MCP (Model Context Protocol) is an open standard that defines a consistent way for applications to share relevant context and information with Large Language Models (LLMs). MCP servers expose specific capabilities through the standardized Model Context Protocol. For more information on MCP, refer to the MCP documentation.

The Endor Labs MCP server integrates seamlessly into your development workflow, scanning your code as you write. You can catch issues long before they’re a problem in production. It plugs directly into your IDE, tightening the feedback loop for both human and AI-generated code. Thus, you can quickly secure your code from the start. With Endor Labs, you’re bringing security all the way left, getting real-time, proactive insights and automated fixes in your editor, while you build, minimizing last-minute security scrambles.

How Endor Labs MCP server helps your development workflow

How to use the Endor Labs MCP server

Choose your IDE or platform to get started

The Endor Labs MCP server integrates directly into Cursor to scan your code as you write, catching security issues before they reach production.

The following sections walk you through setting up the Endor Labs MCP server:

• Prerequisites for Endor Labs MCP server
• One-click installation
• Tools in the Endor Labs MCP server
• Choose your edition
• Developer Edition
• Enterprise Edition
• Manage MCP server tools
• Configure Cursor rules
• Troubleshooting

Prerequisites for Endor Labs MCP server

Ensure that the following prerequisites are met:

• Cursor
• Node.js version 18 or later (required if you don’t have endorctl installed)
• Windows users: See Prerequisites for Endor Labs MCP server on Windows for additional instructions

One-click installation

Select your edition, fill in any required fields, and click Install in Cursor to add the Endor Labs MCP server directly to Cursor.

Tools in the Endor Labs MCP server

Choose your edition

The Endor Labs MCP server has two editions:

• Developer Edition: A free edition that requires no configuration. A browser window opens on first use for authentication via GitHub, GitLab, or Google. The Developer Edition provides access to default security policies from Endor Labs.
• Enterprise Edition: A paid edition that enforces your organization’s specific security policies. Authenticate using GitHub, GitLab, Google, or SSO. You must specify your namespace to access your organization’s policies.

Additionally, if you already have Endor Labs configured locally (for example, from a previous endorctl init command), the MCP server can use your pre-existing configuration.

Developer Edition

You can use the one-click installation tool above or set up the MCP server manually.

Developer Edition: Set up manually

If you prefer to configure the MCP server manually, add the configuration to a .cursor/mcp.json file in the root of your repository (not your home directory).

1. Navigate to the root of your repository.

2. Create a .cursor directory if it doesn’t exist and create an mcp.json file in the .cursor directory.

   mkdir -p .cursor && touch .cursor/mcp.json
   

3. Add the following configuration to the .cursor/mcp.json file.

   {
     "mcpServers": {
       "endor-cli-tools": {
         "command": "npx",
         "args": [
           "-y",
           "endorctl",
           "ai-tools",
           "mcp-server"
         ]
       }
     }
   }
   

Developer Edition: Verify the installation

1. Navigate to Settings > Cursor Settings > Tools & MCP.

2. Confirm that endor-cli-tools appears in the list and is enabled.

Try a test prompt

After installing the MCP server, try the following prompt in your AI chat or CLI to verify that the tools are working.

Check if the npm package lodash version 4.17.20 has any vulnerabilities

The MCP server uses the check_dependency_for_vulnerabilities tool to check for known vulnerabilities and return the results. If you see a response with vulnerability details, the MCP server is working correctly.

Enterprise Edition

For Enterprise Edition, you need your organization’s Endor Labs namespace and an authentication method. Ensure that your developers have Read-Only permissions to Endor Labs. See Authorization policies for more details.

You can use the one-click installation tool above or set up the MCP server manually.

Enterprise Edition: Set up manually

Add the following configuration to a .cursor/mcp.json file in the root of your repository.

{
  "mcpServers": {
    "endor-cli-tools": {
      "command": "npx",
      "args": [
        "-y",
        "endorctl",
        "ai-tools",
        "mcp-server"
      ],
      "env": {
        "ENDOR_NAMESPACE": "<namespace>",
        "ENDOR_MCP_SERVER_AUTH_MODE": "<google|github|gitlab|sso>",
        "ENDOR_TOKEN": "automatic"
      }
    }
  }
}

Replace <namespace> with your Endor Labs namespace and choose your authentication mode. If you choose sso, you must also add ENDOR_MCP_SERVER_AUTH_TENANT to the env section.

Enterprise Edition: Verify the installation

1. Navigate to Settings > Cursor Settings > Tools & MCP.

2. Confirm that endor-cli-tools appears in the list and is enabled.

Try a test prompt

After installing the MCP server, try the following prompt in your AI chat or CLI to verify that the tools are working.

Check if the npm package lodash version 4.17.20 has any vulnerabilities

The MCP server uses the check_dependency_for_vulnerabilities tool to check for known vulnerabilities and return the results. If you see a response with vulnerability details, the MCP server is working correctly.

Manage MCP server tools

1. Navigate to Settings > Cursor Settings > Tools & MCP.

2. Click the tool that you want to disable under endor-cli-tools.

   Click on a disabled tool to enable it.

Configure Cursor rules

To enhance the MCP server integration, you can add custom rules for your project. These rules are custom prompts specific to your project.

1. Navigate to the root of your repository.

2. In the .cursor/rules directory, create an .mdc file to add specific instructions.

3. Add appropriate rules for your project in the .cursor/rules/endorlabs.mdc file. For example, you can add a rule to check if the code is free from vulnerabilities.

Example Cursor rules

You can use the following Cursor rules as a quick start for the Endor Labs MCP server. Modify the rules to meet your specific organization’s needs. We recommend that you store each cursor rule in a separate file. For more information, refer to the Cursor documentation.

• SCA Rule Example
• Secrets Rule Example
• SAST Rule Example

---
description: "Ensure newly added dependencies are checked for vulnerabilities and project stays clean"
globs: '**/package.json, **/package-lock.json, **/yarn.lock, **/pnpm-lock.yaml, **/requirements.txt, **/Pipfile, **/Pipfile.lock, **/pyproject.toml, **/poetry.lock, **/go.mod, **/go.sum, **/Cargo.toml, **/Cargo.lock, **/pom.xml, **/build.gradle, **/build.gradle.kts, **/gradle.lockfile, **/composer.json, **/composer.lock'
alwaysApply: true
---

# Software Composition Analysis (SCA) Rule (Endor Labs via MCP)
This project uses Endor Labs for automated dependency (SCA) scanning, integrated through the MCP server as configured in `.cursor/mcp.json`.

## Workflow

Every time a manifest or lockfile listed above is created or modified in any way immediately do the following prior to performing your next task.

**Important**: Do not proceed after creating or modifying a manifest file without running this first. Do not write any other code or continue with your existing prompt. This is top priority whenever a manifest file is created or updated.

- Run `endor-cli-tools` using the `check_dependency_for_vulnerabilities` tool via the MCP server.
- Provide the **ecosystem**, **dependency name**, and **version** always when making this tool call. Do not forget to provide a version.
- If a vulnerability or error is identified:
  - Upgrade to the suggested safe version, or
  - Replace the dependency with a non-vulnerable alternative.
  - The AI agent must attempt to automatically correct all detected errors and vulnerabilities before session completion.
- Re-run the check using `endor-cli-tools` to confirm the issue is resolved.
- If an error occurs in any MCP server tool call (such as missing required parameters like version, invalid arguments, or tool invocation failures):
  - The AI agent must review the error, determine the cause, and automatically correct the tool call or input parameters.
  - Re-attempt the tool call with the corrected parameters.
  - Continue this process until the tool call succeeds or it is determined that remediation is not possible, in which case the issue and reason must be reported.

## Notes
- All scans must be performed using the MCP server integration (`endor-cli-tools`) as configured in `.cursor/mcp.json`. Do not invoke `endorctl` directly.
- For troubleshooting, ensure the MCP server is running and `endorctl` is installed and accessible in your environment.

This rule ensures that all dependency changes are evaluated for risk at the time of introduction, and that the project remains clean and secure after each coding session. The scan may be performed at the end of an agent session, provided all modifications are checked and remediated before session completion.

---
description: "Scan for leaked secrets on file modification"
globs: '**/*'
alwaysApply: true
---

# Leaked Secrets Detection Rule (Endor Labs via MCP)
This project uses @Endor Labs for automated security scanning, integrated through the MCP server as configured in `.cursor/mcp.json`.

## Workflow
Whenever a file is modified in the repository, and before the end of an agent session:
- Run `endor-cli-tools` using the `scan` tool via the MCP server to check for leaked secrets.
- Ensure the scan includes all file types and respects `.gitignore` unless otherwise configured.
- If any secrets or errors are detected:
  - Remove the exposed secret or correct the error immediately.
  - The AI agent must attempt to automatically correct all detected secrets and errors before session completion.
  - Re-run the scan to verify the secret or error has been properly removed or resolved.
- If an error occurs in any MCP server tool call (such as missing required parameters like version, invalid arguments, or tool invocation failures):
  - The AI agent must review the error, determine the cause, and automatically correct the tool call or input parameters.
  - Re-attempt the tool call with the corrected parameters.
  - Continue this process until the tool call succeeds or it is determined that remediation is not possible, in which case the issue and reason must be reported.
- Save scan results and remediation steps in a security log or as comments for audit purposes.

## Notes
- All scans must be performed using the MCP server integration (`endor-cli-tools`) as configured in `.cursor/mcp.json`. Do not invoke `endorctl` directly.
- For troubleshooting, ensure the MCP server is running and `endorctl` is installed and accessible in your environment.
- **Important**: This scan must use the path of the directory from which the changed files are in. Do not attempt to set the path directly to a file as it must be a directory. Use absolute paths like /Users/username/mcp-server-demo/backend rather than relative paths like 'backend'

This rule ensures no accidental credentials, tokens, API keys, or secrets are committed or remain in the project history. The scan may be performed at the end of an agent session, provided all modifications are checked and remediated before session completion.

---
description: "Run SAST scan using endor-cli-tools on source code changes"
globs: '**/*.c, **/*.cpp, **/*.cc, **/*.cs, **/*.go, **/*.java, **/*.js, **/*.jsx, **/*.ts, **/*.tsx, **/*.py, **/*.php, **/*.rb, **/*.rs, **/*.kt, **/*.kts, **/*.scala, **/*.swift, **/*.dart, **/*.html, **/*.yaml, **/*.yml, **/*.json, **/*.xml, **/*.sh, **/*.bash, **/*.clj, **/*.cljs, **/*.ex, **/*.exs, **/*.lua'
alwaysApply: true
---

# Static Application Security Testing (SAST) Rule (Endor Labs via MCP)

This project uses @Endor Labs for automated SAST, integrated through the MCP server as configured in `.cursor/mcp.json`.

## Workflow

Whenever a file is modified in the repository, and before the end of an agent session perform the following workflow:

- Run `endor-cli-tools` using the `scan` tool via the MCP server to perform SAST scans as described above.
- If any vulnerabilities or errors are found:
  - Present the issues to the user.
  - The AI agent must attempt to automatically correct all errors and vulnerabilities, including code errors, security issues, and best practice violations, before session completion.
  - Recommend and apply appropriate fixes (e.g., input sanitization, validation, escaping, secure APIs).
  - Continue scanning and correcting until all critical issues have been resolved or no further automated remediation is possible.
- If an error occurs in any MCP server tool call (such as missing required parameters like version, invalid arguments, or tool invocation failures):
  - The AI agent must review the error, determine the cause, and automatically correct the tool call or input parameters.
  - Re-attempt the tool call with the corrected parameters.
  - Continue this process until the tool call succeeds or it is determined that remediation is not possible, in which case the issue and reason must be reported.
- Save scan results and remediation steps in a security log or as comments for audit purposes.

## Notes
- All scans must be performed using the MCP server integration (`endor-cli-tools`) as configured in `.cursor/mcp.json`. Do not invoke `endorctl` directly.
- For troubleshooting, ensure the MCP server is running and `endorctl` is installed and accessible in your environment.
- Do not invoke Opengrep directly.
- **Important**: This scan must use the path of the directory from which the changed files are in. Do not attempt to set the path directly to a file as it must be a directory. Use absolute paths like /Users/username/mcp-server-demo/backend rather than relative paths like 'backend'

This rule ensures all code changes are automatically reviewed and remediated for common security vulnerabilities and errors using `endor-cli-tools` and the MCP server, with Opengrep as the underlying engine.

Watch how to use Endor Labs with Cursor

Troubleshooting

"command": "endorctl",
"args": ["ai-tools", "mcp-server"]

Prerequisites for Endor Labs MCP server on Windows

npx --version

The Endor Labs MCP server integrates directly into Claude Code to scan your code as you write, catching security issues before they reach production.

The following sections walk you through setting up the Endor Labs MCP server:

• Prerequisites for Endor Labs MCP server
• Interactive setup
• Tools in the Endor Labs MCP server
• Choose your edition
• Developer Edition
• Enterprise Edition
• Scope options
• Manage MCP servers
• Configure CLAUDE.md
• Troubleshooting

Prerequisites for Endor Labs MCP server

Ensure that the following prerequisites are met:

• Claude Code
• Node.js version 18 or later (required if you don’t have endorctl installed)
• Windows users: See Prerequisites for Endor Labs MCP server on Windows for additional instructions

Interactive setup

Select your edition, fill in any required fields, and click Copy to get the command that adds the Endor Labs MCP server to Claude Code.

Tools in the Endor Labs MCP server

Choose your edition

The Endor Labs MCP server has two editions:

• Developer Edition: A free edition that requires no configuration. A browser window opens on first use for authentication via GitHub, GitLab, or Google. The Developer Edition provides access to default security policies from Endor Labs.
• Enterprise Edition: A paid edition that enforces your organization’s specific security policies. Authenticate using GitHub, GitLab, Google, or SSO. You must specify your namespace to access your organization’s policies.

Additionally, if you already have Endor Labs configured locally (for example, from a previous endorctl init command), the MCP server can use your pre-existing configuration.

Developer Edition

Developer Edition: Add the MCP server with a single command

Run the following command to add the MCP server to your project. This adds the server with --scope local (available only to you in the current project). See Scope options for other scopes.

claude mcp add endor-cli-tools -- npx -y endorctl ai-tools mcp-server

Developer Edition: Add the MCP server with .mcp.json configuration

Create an .mcp.json file in the root of your repository and add the following configuration. This uses project scope, which is shared with everyone working on the repository.

{
  "mcpServers": {
    "endor-cli-tools": {
      "command": "npx",
      "args": [
        "-y",
        "endorctl",
        "ai-tools",
        "mcp-server"
      ]
    }
  }
}

Developer Edition: Verify the installation

claude mcp list

Confirm that endor-cli-tools appears in the list. You can also use /mcp in Claude Code to view active MCP servers.

Try a test prompt

After installing the MCP server, try the following prompt in your AI chat or CLI to verify that the tools are working.

Check if the npm package lodash version 4.17.20 has any vulnerabilities

The MCP server uses the check_dependency_for_vulnerabilities tool to check for known vulnerabilities and return the results. If you see a response with vulnerability details, the MCP server is working correctly.

Enterprise Edition

For Enterprise Edition, you need your organization’s Endor Labs namespace and an authentication method. Ensure that your developers have Read-Only permissions to Endor Labs. See Authorization policies for more details.

Enterprise Edition: Add the MCP server with a single command

claude mcp add --transport stdio --scope user \
  --env ENDOR_NAMESPACE=<namespace> \
  --env ENDOR_MCP_SERVER_AUTH_MODE=<google|github|gitlab|sso> \
  --env ENDOR_TOKEN=automatic \
  endor-cli-tools -- npx -y endorctl ai-tools mcp-server

If you want to use SSO authentication, you must also add ENDOR_MCP_SERVER_AUTH_TENANT to the environment variables.

claude mcp add --transport stdio --scope user \
  --env ENDOR_NAMESPACE=my-org \
  --env ENDOR_MCP_SERVER_AUTH_MODE=sso \
  --env ENDOR_MCP_SERVER_AUTH_TENANT=my-tenant \
  --env ENDOR_TOKEN=automatic \
  endor-cli-tools -- npx -y endorctl ai-tools mcp-server

For example, if your Endor Labs namespace is my-org and you want to use Google authentication, run the following command:

claude mcp add --transport stdio --scope user \
  --env ENDOR_NAMESPACE=my-org \
  --env ENDOR_MCP_SERVER_AUTH_MODE=google \
  --env ENDOR_TOKEN=automatic \
  endor-cli-tools -- npx -y endorctl ai-tools mcp-server

Enterprise Edition: Add the MCP server with .mcp.json configuration

Create an .mcp.json file in the root of your repository and add the following configuration to add the MCP server to your project.

{
  "mcpServers": {
    "endor-cli-tools": {
      "command": "npx",
      "args": [
        "-y",
        "endorctl",
        "ai-tools",
        "mcp-server"
      ],
      "env": {
        "ENDOR_NAMESPACE": "<namespace>",
        "ENDOR_MCP_SERVER_AUTH_MODE": "<google|github|gitlab|sso>",
        "ENDOR_TOKEN": "automatic"
      }
    }
  }
}

If you want to use SSO authentication, you must also add ENDOR_MCP_SERVER_AUTH_TENANT to the env section.

{
  "mcpServers": {
    "endor-cli-tools": {
      "command": "npx",
      "args": [
        "-y",
        "endorctl",
        "ai-tools",
        "mcp-server"
      ],
      "env": {
        "ENDOR_NAMESPACE": "<namespace>",
        "ENDOR_MCP_SERVER_AUTH_MODE": "sso",
        "ENDOR_MCP_SERVER_AUTH_TENANT": "<tenant>",
        "ENDOR_TOKEN": "automatic"
      }
    }
  }
}

Replace <namespace> with your Endor Labs namespace and choose your authentication mode.

Enterprise Edition: Verify the installation

claude mcp list

Confirm that endor-cli-tools appears in the list. You can also use /mcp in Claude Code to view active MCP servers.

Try a test prompt

After installing the MCP server, try the following prompt in your AI chat or CLI to verify that the tools are working.

Check if the npm package lodash version 4.17.20 has any vulnerabilities

The MCP server uses the check_dependency_for_vulnerabilities tool to check for known vulnerabilities and return the results. If you see a response with vulnerability details, the MCP server is working correctly.

Scope options

Claude Code supports three MCP configuration scopes:

• --scope local: Available only to you in the current project (default).
• --scope project: Shared with everyone in the project via .mcp.json file.
• --scope user: Available to you across all projects.

Manage MCP servers

claude mcp list
claude mcp get endor-cli-tools
claude mcp remove endor-cli-tools

In Claude Code, use /mcp to view and manage your active MCP servers.

Configure CLAUDE.md

To enhance the MCP server integration, you can add instructions in CLAUDE.md at the root of your repository. Claude Code reads CLAUDE.md files to guide AI development with your project-specific instructions.

1. Navigate to the root of your repository.

2. Create or edit the CLAUDE.md file in the root of your repository.

3. Add appropriate rules for your project. For example, you can add a rule to check if the code is free from vulnerabilities.

Example CLAUDE.md instructions

You can use the following CLAUDE.md instructions as a quick start for the Endor Labs MCP server. Modify the instructions to meet your specific organization’s needs. For more information, refer to the Claude Code documentation.

• SCA Rule Example
• Secrets Rule Example
• SAST Rule Example

# Software Composition Analysis (SCA) Rule (Endor Labs via MCP)

This project uses Endor Labs for automated dependency (SCA) scanning, integrated through the MCP server.

## Workflow

Every time a manifest or lockfile (package.json, requirements.txt, go.mod, pom.xml, etc.) is created or modified in any way, immediately do the following prior to performing your next task.

**Important**: Do not proceed after creating or modifying a manifest file without running this first.

- Run `endor-cli-tools` using the `check_dependency_for_vulnerabilities` tool via the MCP server.
- Provide the **ecosystem**, **dependency name**, and **version** always when making this tool call.
- If a vulnerability or error is identified:
  - Upgrade to the suggested safe version, or
  - Replace the dependency with a non-vulnerable alternative.
- Re-run the check using `endor-cli-tools` to confirm the issue is resolved.

## Notes
- All scans must be performed using the MCP server integration (`endor-cli-tools`). Do not invoke `endorctl` directly.

# Leaked Secrets Detection Rule (Endor Labs via MCP)

This project uses [Endor Labs](https://docs.endorlabs.com/) for automated security scanning, integrated through the MCP server.

## Workflow

Whenever a file is modified in the repository, and before the end of an agent session:

- Run `endor-cli-tools` using the `scan` tool via the MCP server to check for leaked secrets.
- If any secrets or errors are detected:
  - Remove the exposed secret or correct the error immediately.
  - Re-run the scan to verify the secret has been properly removed.
- Save scan results and remediation steps in a security log or as comments for audit purposes.

## Notes
- All scans must be performed using the MCP server integration (`endor-cli-tools`). Do not invoke `endorctl` directly.
- This scan must use the path of the directory from which the changed files are in. Use absolute paths.

# Static Application Security Testing (SAST) Rule (Endor Labs via MCP)

This project uses [Endor Labs](https://docs.endorlabs.com/) for automated SAST, integrated through the MCP server.

## Workflow

Whenever a file is modified in the repository, and before the end of an agent session:

- Run `endor-cli-tools` using the `scan` tool via the MCP server to perform SAST scans.
- If any vulnerabilities or errors are found:
  - Present the issues to the user.
  - Recommend and apply appropriate fixes (e.g., input sanitization, validation, escaping, secure APIs).
- Save scan results and remediation steps in a security log or as comments for audit purposes.

## Notes
- All scans must be performed using the MCP server integration (`endor-cli-tools`). Do not invoke `endorctl` directly.
- Do not invoke Opengrep directly.
- This scan must use the path of the directory from which the changed files are in. Use absolute paths.

Watch how to use Endor Labs with Claude Code

Troubleshooting

"command": "endorctl",
"args": ["ai-tools", "mcp-server"]

Prerequisites for Endor Labs MCP server on Windows

npx --version

The Endor Labs MCP server integrates directly into OpenAI Codex to scan your code as you write, catching security issues before they reach production.

The following sections walk you through setting up the Endor Labs MCP server:

• Prerequisites for Endor Labs MCP server
• Interactive setup
• Tools in the Endor Labs MCP server
• Choose your edition
• Developer Edition
• Enterprise Edition
• Manage MCP server tools
• Configure AGENTS.md
• Troubleshooting

Prerequisites for Endor Labs MCP server

Ensure that the following prerequisites are met:

• OpenAI Codex CLI
• Node.js version 18 or later (required if you don’t have endorctl installed)
• Windows users: See Prerequisites for Endor Labs MCP server on Windows for additional instructions

Interactive setup

Select your edition, fill in any required fields, and click Copy to get the command that adds the Endor Labs MCP server to OpenAI Codex.

Tools in the Endor Labs MCP server

Choose your edition

The Endor Labs MCP server has two editions:

• Developer Edition: A free edition that requires no configuration. A browser window opens on first use for authentication via GitHub, GitLab, or Google. The Developer Edition provides access to default security policies from Endor Labs.
• Enterprise Edition: A paid edition that enforces your organization’s specific security policies. Authenticate using GitHub, GitLab, Google, or SSO. You must specify your namespace to access your organization’s policies.

Additionally, if you already have Endor Labs configured locally (for example, from a previous endorctl init command), the MCP server can use your pre-existing configuration.

Developer Edition

Developer Edition: Add the MCP server with a single command

Run the following command to add the MCP server to your project.

codex mcp add endor-cli-tools -- npx -y endorctl ai-tools mcp-server

Developer Edition: Add the MCP server with config.toml

Add the following to your ~/.codex/config.toml (or a project-scoped .codex/config.toml).

[mcp_servers.endor-cli-tools]
command = "npx"
args = ["-y", "endorctl", "ai-tools", "mcp-server"]

Developer Edition: Verify the installation

codex mcp list

Confirm that endor-cli-tools appears in the list. You can also use /mcp in the Codex TUI to view active MCP servers.

Try a test prompt

After installing the MCP server, try the following prompt in your AI chat or CLI to verify that the tools are working.

Check if the npm package lodash version 4.17.20 has any vulnerabilities

The MCP server uses the check_dependency_for_vulnerabilities tool to check for known vulnerabilities and return the results. If you see a response with vulnerability details, the MCP server is working correctly.

Enterprise Edition

For Enterprise Edition, you need your organization’s Endor Labs namespace and an authentication method. Ensure that your developers have Read-Only permissions to Endor Labs. See Authorization policies for more details.

Enterprise Edition: Add the MCP server with a single command

codex mcp add endor-cli-tools \
  --env ENDOR_NAMESPACE=<namespace> \
  --env ENDOR_MCP_SERVER_AUTH_MODE=<google|github|gitlab|sso> \
  --env ENDOR_TOKEN=automatic \
  -- npx -y endorctl ai-tools mcp-server

Replace <namespace> with your Endor Labs namespace and choose your authentication mode. If you choose sso, you must also add ENDOR_MCP_SERVER_AUTH_TENANT to the environment variables.

Enterprise Edition: Add the MCP server with config.toml

[mcp_servers.endor-cli-tools]
command = "npx"
args = ["-y", "endorctl", "ai-tools", "mcp-server"]

[mcp_servers.endor-cli-tools.env]
ENDOR_NAMESPACE = "<namespace>"
ENDOR_MCP_SERVER_AUTH_MODE = "<google|github|gitlab|sso>"
ENDOR_TOKEN = "automatic"

Replace <namespace> with your Endor Labs namespace and choose your authentication mode. If you choose sso, you must also add ENDOR_MCP_SERVER_AUTH_TENANT to the env section.

Enterprise Edition: Verify the installation

codex mcp list

Confirm that endor-cli-tools appears in the list.

Try a test prompt

After installing the MCP server, try the following prompt in your AI chat or CLI to verify that the tools are working.

Check if the npm package lodash version 4.17.20 has any vulnerabilities

The MCP server uses the check_dependency_for_vulnerabilities tool to check for known vulnerabilities and return the results. If you see a response with vulnerability details, the MCP server is working correctly.

Manage MCP server tools

In the Codex TUI, use /mcp to see your active MCP servers. You can also disable specific tools in the config.toml file:

[mcp_servers.endor-cli-tools]
command = "npx"
args = ["-y", "endorctl", "ai-tools", "mcp-server"]
enabled_tools = ["check_dependency_for_vulnerabilities", "scan"]

Configure AGENTS.md

To enhance the MCP server integration, you can add instructions in AGENTS.md at the root of your repository. Codex reads AGENTS.md files to guide AI development with your project-specific instructions.

1. Navigate to the root of your repository.

2. Create or edit the AGENTS.md file in the root of your repository.

3. Add appropriate rules for your project. For example, you can add a rule to check if the code is free from vulnerabilities.

Example AGENTS.md instructions

You can use the following AGENTS.md instructions as a quick start for the Endor Labs MCP server. Modify the instructions to meet your specific organization’s needs. For more information, refer to the OpenAI Codex AGENTS.md documentation.

• SCA Rule Example
• Secrets Rule Example
• SAST Rule Example

# Software Composition Analysis (SCA) Rule (Endor Labs via MCP)

This project uses Endor Labs for automated dependency (SCA) scanning, integrated through the MCP server.

## Workflow

Every time a manifest or lockfile (package.json, requirements.txt, go.mod, pom.xml, etc.) is created or modified in any way, immediately do the following prior to performing your next task.

**Important**: Do not proceed after creating or modifying a manifest file without running this first.

- Run `endor-cli-tools` using the `check_dependency_for_vulnerabilities` tool via the MCP server.
- Provide the **ecosystem**, **dependency name**, and **version** always when making this tool call.
- If a vulnerability or error is identified:
  - Upgrade to the suggested safe version, or
  - Replace the dependency with a non-vulnerable alternative.
- Re-run the check using `endor-cli-tools` to confirm the issue is resolved.

## Notes
- All scans must be performed using the MCP server integration (`endor-cli-tools`). Do not invoke `endorctl` directly.

# Leaked Secrets Detection Rule (Endor Labs via MCP)

This project uses [Endor Labs](https://docs.endorlabs.com/) for automated security scanning, integrated through the MCP server.

## Workflow

Whenever a file is modified in the repository, and before the end of an agent session:

- Run `endor-cli-tools` using the `scan` tool via the MCP server to check for leaked secrets.
- If any secrets or errors are detected:
  - Remove the exposed secret or correct the error immediately.
  - Re-run the scan to verify the secret has been properly removed.
- Save scan results and remediation steps in a security log or as comments for audit purposes.

## Notes
- All scans must be performed using the MCP server integration (`endor-cli-tools`). Do not invoke `endorctl` directly.
- This scan must use the path of the directory from which the changed files are in. Use absolute paths.

# Static Application Security Testing (SAST) Rule (Endor Labs via MCP)

This project uses [Endor Labs](https://docs.endorlabs.com/) for automated SAST, integrated through the MCP server.

## Workflow

Whenever a file is modified in the repository, and before the end of an agent session:

- Run `endor-cli-tools` using the `scan` tool via the MCP server to perform SAST scans.
- If any vulnerabilities or errors are found:
  - Present the issues to the user.
  - Recommend and apply appropriate fixes (e.g., input sanitization, validation, escaping, secure APIs).
- Save scan results and remediation steps in a security log or as comments for audit purposes.

## Notes
- All scans must be performed using the MCP server integration (`endor-cli-tools`). Do not invoke `endorctl` directly.
- Do not invoke Opengrep directly.
- This scan must use the path of the directory from which the changed files are in. Use absolute paths.

Troubleshooting

"command": "endorctl",
"args": ["ai-tools", "mcp-server"]

Prerequisites for Endor Labs MCP server on Windows

npx --version

The Endor Labs MCP server integrates directly into Visual Studio Code to scan your code as you write, catching security issues before they reach production.

The following sections walk you through setting up the Endor Labs MCP server:

• Prerequisites for Endor Labs MCP server
• One-click installation
• Tools in the Endor Labs MCP server
• Choose your edition
• Developer Edition
• Enterprise Edition
• Manage MCP server tools
• Use the MCP server with GitHub Copilot
• Example Copilot rules
• Troubleshooting

Prerequisites for Endor Labs MCP server

Ensure that the following prerequisites are met:

• Visual Studio Code version 1.99 or later
• MCP support enabled: set chat.mcp.enabled to true in your Visual Studio Code settings
• Node.js version 18 or later (required if you don’t have endorctl installed)
• Windows users: See Prerequisites for Endor Labs MCP server on Windows for additional instructions

One-click installation

Select your edition, fill in any required fields, and click Install in VS Code to add the Endor Labs MCP server directly to Visual Studio Code.

Tools in the Endor Labs MCP server

Choose your edition

The Endor Labs MCP server has two editions:

• Developer Edition: A free edition that requires no configuration. A browser window opens on first use for authentication via GitHub, GitLab, or Google. The Developer Edition provides access to default security policies from Endor Labs.
• Enterprise Edition: A paid edition that enforces your organization’s specific security policies. Authenticate using GitHub, GitLab, Google, or SSO. You must specify your namespace to access your organization’s policies.

Additionally, if you already have Endor Labs configured locally (for example, from a previous endorctl init command), the MCP server can use your pre-existing configuration.

Developer Edition

You can use the one-click installation tool above or set up the MCP server manually.

Developer Edition: Manual installation

If you prefer to configure the MCP server manually, add the configuration to a .vscode/mcp.json file in the root of your repository.

1. Navigate to the root of your repository.

2. Create a .vscode directory if it doesn’t exist and create an mcp.json file in the .vscode directory.

   mkdir -p .vscode && touch .vscode/mcp.json
   

3. Add the following configuration to the .vscode/mcp.json file.

   {
     "servers": {
       "endor-cli-tools": {
         "command": "npx",
         "args": [
           "-y",
           "endorctl",
           "ai-tools",
           "mcp-server"
         ]
       }
     }
   }
   

Developer Edition: Verify the installation

1. Open the Chat view by pressing Cmd+Option+I (macOS) or Ctrl+Alt+I (Windows/Linux).

2. Switch to Agent mode.

3. Click the Settings icon and confirm that MCP Server: endor-cli-tools appears and is enabled.

Try a test prompt

After installing the MCP server, try the following prompt in your AI chat or CLI to verify that the tools are working.

Check if the npm package lodash version 4.17.20 has any vulnerabilities

The MCP server uses the check_dependency_for_vulnerabilities tool to check for known vulnerabilities and return the results. If you see a response with vulnerability details, the MCP server is working correctly.

Enterprise Edition

For Enterprise Edition, you need your organization’s Endor Labs namespace and an authentication method. Ensure that your developers have Read-Only permissions to Endor Labs. See Authorization policies for more details.

You can use the one-click installation tool above or set up the MCP server manually.

Enterprise Edition: Manual installation

Add the following configuration to a .vscode/mcp.json file in the root of your repository.

{
  "servers": {
    "endor-cli-tools": {
      "command": "npx",
      "args": [
        "-y",
        "endorctl",
        "ai-tools",
        "mcp-server"
      ],
      "env": {
        "ENDOR_NAMESPACE": "<namespace>",
        "ENDOR_MCP_SERVER_AUTH_MODE": "<google|github|gitlab|sso>",
        "ENDOR_TOKEN": "automatic"
      }
    }
  }
}

Replace <namespace> with your Endor Labs namespace and choose your authentication mode. If you choose sso, you must also add ENDOR_MCP_SERVER_AUTH_TENANT to the env section.

Enterprise Edition: Verify the installation

1. Open the Chat view by pressing Cmd+Option+I (macOS) or Ctrl+Alt+I (Windows/Linux).

2. Switch to Agent mode.

3. Click the Settings icon and confirm that MCP Server: endor-cli-tools appears and is enabled.

Try a test prompt

After installing the MCP server, try the following prompt in your AI chat or CLI to verify that the tools are working.

Check if the npm package lodash version 4.17.20 has any vulnerabilities

The MCP server uses the check_dependency_for_vulnerabilities tool to check for known vulnerabilities and return the results. If you see a response with vulnerability details, the MCP server is working correctly.

Manage MCP server tools

1. Open the Chat view by pressing Cmd+Option+I.

2. Switch to the Agent mode.

3. Click the Settings icon.

4. Select the tools that you want to enable or disable under MCP Server: endor-cli-tools.

Use the MCP server with GitHub Copilot

To use the Endor Labs MCP server with GitHub Copilot in Visual Studio Code:

1. Open the Chat view by pressing Cmd+Option+I.

2. Switch to the Agent mode.

3. Click the Settings icon.

4. Select MCP Server: endor-cli-tools from the dropdown menu.

5. Set up Copilot rules in .github/instructions/*.md to use the Endor Labs MCP server throughout the development process. See Example Copilot rules for more information.

You can now use Endor Labs tools in your chat prompts to scan for vulnerabilities.

Example Copilot rules

Copilot instructions define the guidelines that Copilot should follow throughout the development process. The following examples demonstrate how to use the Endor Labs MCP server within Copilot rules.

• SCA Rule Example
• Secrets Rule Example
• SAST Rule Example

---
description: "Ensure newly added dependencies are checked for vulnerabilities and project stays clean"
applyTo: '**/package.json, **/package-lock.json, **/yarn.lock, **/pnpm-lock.yaml, **/requirements.txt, **/Pipfile, **/Pipfile.lock, **/pyproject.toml, **/poetry.lock, **/go.mod, **/go.sum, **/Cargo.toml, **/Cargo.lock, **/pom.xml, **/build.gradle, **/build.gradle.kts, **/gradle.lockfile, **/composer.json, **/composer.lock'
alwaysApply: true
---

# Software Composition Analysis (SCA) Rule (Endor Labs via MCP)
This project uses Endor Labs for automated dependency (SCA) scanning, integrated through the MCP server as configured in `.vscode/mcp.json`.

## Workflow

Every time a manifest or lockfile listed above is created or modified in any way immediately do the following prior to performing your next task.

**Important**: Do not proceed after creating or modifying a manifest file without running this first. Do not write any other code or continue with your existing prompt. This is top priority whenever a manifest file is created or updated.

- Run `endor-cli-tools` using the `check_dependency_for_vulnerabilities` tool via the MCP server.
- Provide the **ecosystem**, **dependency name**, and **version** always when making this tool call. Do not forget to provide a version.
- If a vulnerability or error is identified:
  - Upgrade to the suggested safe version, or
  - Replace the dependency with a non-vulnerable alternative.
  - The AI agent must attempt to automatically correct all detected errors and vulnerabilities before session completion.
- Re-run the check using `endor-cli-tools` to confirm the issue is resolved.
- If an error occurs in any MCP server tool call (such as missing required parameters like version, invalid arguments, or tool invocation failures):
  - The AI agent must review the error, determine the cause, and automatically correct the tool call or input parameters.
  - Re-attempt the tool call with the corrected parameters.
  - Continue this process until the tool call succeeds or it is determined that remediation is not possible, in which case the issue and reason must be reported.

## Notes
- All scans must be performed using the MCP server integration (`endor-cli-tools`) as configured in `.vscode/mcp.json`. Do not invoke `endorctl` directly.
- For troubleshooting, ensure the MCP server is running and `endorctl` is installed and accessible in your environment.

This rule ensures that all dependency changes are evaluated for risk at the time of introduction, and that the project remains clean and secure after each coding session. The scan may be performed at the end of an agent session, provided all modifications are checked and remediated before session completion.

---
description: "Scan for leaked secrets on file modification"
applyTo: '**/*'
alwaysApply: true
---

# Leaked Secrets Detection Rule (Endor Labs via MCP)
This project uses @Endor Labs for automated security scanning, integrated through the MCP server as configured in `.vscode/mcp.json`.

## Workflow
Whenever a file is modified in the repository, and before the end of an agent session:
- Run `endor-cli-tools` using the `scan` tool via the MCP server to check for leaked secrets.
- Ensure the scan includes all file types and respects `.gitignore` unless otherwise configured.
- If any secrets or errors are detected:
  - Remove the exposed secret or correct the error immediately.
  - The AI agent must attempt to automatically correct all detected secrets and errors before session completion.
  - Re-run the scan to verify the secret or error has been properly removed or resolved.
- If an error occurs in any MCP server tool call (such as missing required parameters like version, invalid arguments, or tool invocation failures):
  - The AI agent must review the error, determine the cause, and automatically correct the tool call or input parameters.
  - Re-attempt the tool call with the corrected parameters.
  - Continue this process until the tool call succeeds or it is determined that remediation is not possible, in which case the issue and reason must be reported.
- Save scan results and remediation steps in a security log or as comments for audit purposes.

## Notes
- All scans must be performed using the MCP server integration (`endor-cli-tools`) as configured in `.vscode/mcp.json`. Do not invoke `endorctl` directly.
- For troubleshooting, ensure the MCP server is running and `endorctl` is installed and accessible in your environment.
- **Important**: This scan must use the path of the directory from which the changed files are in. Do not attempt to set the path directly to a file as it must be a directory. Use absolute paths like /Users/username/mcp-server-demo/backend rather than relative paths like 'backend'

This rule ensures no accidental credentials, tokens, API keys, or secrets are committed or remain in the project history. The scan may be performed at the end of an agent session, provided all modifications are checked and remediated before session completion.

---
description: "Run SAST scan using endor-cli-tools on source code changes"
applyTo: '**/*.c, **/*.cpp, **/*.cc, **/*.cs, **/*.go, **/*.java, **/*.js, **/*.jsx, **/*.ts, **/*.tsx, **/*.py, **/*.php, **/*.rb, **/*.rs, **/*.kt, **/*.kts, **/*.scala, **/*.swift, **/*.dart, **/*.html, **/*.yaml, **/*.yml, **/*.json, **/*.xml, **/*.sh, **/*.bash, **/*.clj, **/*.cljs, **/*.ex, **/*.exs, **/*.lua'
alwaysApply: true
---

# Static Application Security Testing (SAST) Rule (Endor Labs via MCP)

This project uses @Endor Labs for automated SAST, integrated through the MCP server as configured in `.vscode/mcp.json`.

## Workflow

Whenever a file is modified in the repository, and before the end of an agent session perform the following workflow:

- Run `endor-cli-tools` using the `scan` tool via the MCP server to perform SAST scans as described above.
- If any vulnerabilities or errors are found:
  - Present the issues to the user.
  - The AI agent must attempt to automatically correct all errors and vulnerabilities, including code errors, security issues, and best practice violations, before session completion.
  - Recommend and apply appropriate fixes (e.g., input sanitization, validation, escaping, secure APIs).
  - Continue scanning and correcting until all critical issues have been resolved or no further automated remediation is possible.
- If an error occurs in any MCP server tool call (such as missing required parameters like version, invalid arguments, or tool invocation failures):
  - The AI agent must review the error, determine the cause, and automatically correct the tool call or input parameters.
  - Re-attempt the tool call with the corrected parameters.
  - Continue this process until the tool call succeeds or it is determined that remediation is not possible, in which case the issue and reason must be reported.
- Save scan results and remediation steps in a security log or as comments for audit purposes.

## Notes
- All scans must be performed using the MCP server integration (`endor-cli-tools`) as configured in `.vscode/mcp.json`. Do not invoke `endorctl` directly.
- For troubleshooting, ensure the MCP server is running and `endorctl` is installed and accessible in your environment.
- Do not invoke Opengrep directly.
- **Important**: This scan must use the path of the directory from which the changed files are in. Do not attempt to set the path directly to a file as it must be a directory. Use absolute paths like /Users/username/mcp-server-demo/backend rather than relative paths like 'backend'

This rule ensures all code changes are automatically reviewed and remediated for common security vulnerabilities and errors using `endor-cli-tools` and the MCP server, with Opengrep as the underlying engine.

Watch how to use Endor Labs with Visual Studio Code

Troubleshooting

"command": "endorctl",
"args": ["ai-tools", "mcp-server"]

Prerequisites for Endor Labs MCP server on Windows

npx --version

The Endor Labs MCP server integrates directly into Devin to scan your code as you write, catching security issues before they reach production.

The following sections walk you through setting up the Endor Labs MCP server:

• Prerequisites for Endor Labs MCP server
• Tools in the Endor Labs MCP server
• Add Endor Labs MCP server through the MCP Marketplace
• Manage MCP server tools
• Configure Devin Knowledge
• Troubleshooting

Prerequisites for Endor Labs MCP server

Ensure that the following prerequisites are met:

• A Devin account with access to the MCP Marketplace
• Your organization’s Endor Labs namespace
• Endor Labs API key and secret. See Endor Labs’ API keys for more information

Tools in the Endor Labs MCP server

Add Endor Labs MCP server through the MCP Marketplace

1. Navigate to Settings > MCP Marketplace in Devin.

2. Click Add Your Own to add a custom MCP server.

3. Add the following secrets with the corresponding values:

   • ENDOR_API_CREDENTIALS_KEY: Your Endor Labs API key
   • ENDOR_API_CREDENTIALS_SECRET: Your Endor Labs API secret
   • ENDOR_NAMESPACE: Your Endor Labs namespace

4. Add the following configuration under STDIO Configuration:

   • Command: npx
   • Arguments: -y endorctl ai-tools mcp-server -n $ENDOR_NAMESPACE --api-key $ENDOR_API_CREDENTIALS_KEY --api-secret $ENDOR_API_CREDENTIALS_SECRET

5. Click Save Changes to save the MCP server configuration.

Configuration parameters

The following parameters are used to configure the MCP server in Devin:

• ENDOR_API_CREDENTIALS_KEY: (Required) Your Endor Labs API key. See API keys for more information.
• ENDOR_API_CREDENTIALS_SECRET: (Required) Your Endor Labs API secret.
• ENDOR_NAMESPACE: (Required) Your Endor Labs namespace to access your organization’s policies.

Manage MCP server tools

1. Navigate to Settings > MCP Marketplace in Devin.

2. Locate the endor-cli-tools server in the list.

3. Click the server to view its details and manage its tools.

Configure Devin Knowledge

To enhance the MCP server integration, you can add instructions through Devin Knowledge. Knowledge entries guide Devin’s AI development with your project-specific instructions.

1. Navigate to Settings > Knowledge in Devin.

2. Create a new Knowledge entry for Endor Labs security scanning.

3. Add appropriate instructions for your project. For example, you can add a rule to check if the code is free from vulnerabilities.

You can also create a Playbook to automate security scanning workflows with the Endor Labs MCP server.

Example Knowledge instructions

You can use the following Knowledge instructions as a quick start for the Endor Labs MCP server. Modify the instructions to meet your specific organization’s needs. For more information, refer to the Devin Knowledge documentation.

• SCA Rule Example
• Secrets Rule Example
• SAST Rule Example

# Software Composition Analysis (SCA) Rule (Endor Labs MCP server)

This project uses Endor Labs for automated dependency (SCA) scanning, integrated through the MCP server.

## Workflow

Every time a manifest or lockfile (`package.json`, `requirements.txt`, `go.mod`, `pom.xml`, etc.) is created or modified in any way, immediately do the following prior to performing your next task.

**Important**: Do not proceed after creating or modifying a manifest file without running this first.

- Run `endor-cli-tools` using the `check_dependency_for_vulnerabilities` tool via the MCP server.
- Provide the **ecosystem**, **dependency name**, and **version** always when making this tool call.
- If a vulnerability or error is identified:
  - Upgrade to the suggested safe version, or
  - Replace the dependency with a non-vulnerable alternative.
- Re-run the check using `endor-cli-tools` to confirm the issue is resolved.

## Notes
- All scans must be performed using the MCP server integration (`endor-cli-tools`). Do not invoke `endorctl` directly.

# Leaked Secrets Detection Rule (Endor Labs MCP server)

This project uses Endor Labs for automated security scanning, integrated through the MCP server.

## Workflow

Whenever a file is modified in the repository, and before the end of a session:

- Run `endor-cli-tools` using the `scan` tool via the MCP server to check for leaked secrets.
- If any secrets or errors are detected:
  - Remove the exposed secret or correct the error immediately.
  - Re-run the scan to verify the secret has been properly removed.
- Save scan results and remediation steps in a security log or as comments for audit purposes.

## Notes
- All scans must be performed using the MCP server integration (`endor-cli-tools`). Do not invoke `endorctl` directly.
- This scan must use the path of the directory from which the changed files are in. Use absolute paths.

# Static Application Security Testing (SAST) Rule (Endor Labs MCP server)

This project uses Endor Labs for automated SAST, integrated through the MCP server.

## Workflow

Whenever a file is modified in the repository, and before the end of a session:

- Run `endor-cli-tools` using the `scan` tool via the MCP server to perform SAST scans.
- If any vulnerabilities or errors are found:
  - Present the issues to the user.
  - Recommend and apply appropriate fixes (e.g., input sanitization, validation, escaping, secure APIs).
- Save scan results and remediation steps in a security log or as comments for audit purposes.

## Notes
- All scans must be performed using the MCP server integration (`endor-cli-tools`). Do not invoke `endorctl` directly.
- Do not invoke Opengrep directly.
- This scan must use the path of the directory from which the changed files are in. Use absolute paths.

Watch how to use Endor Labs with Devin

Troubleshooting

"command": "endorctl",
"args": ["ai-tools", "mcp-server"]

The Endor Labs MCP server integrates directly into Gemini CLI to scan your code as you write, catching security issues before they reach production.

You can either install the MCP server as a Gemini extension or with Gemini CLI.

The following sections walk you through setting up the Endor Labs MCP server:

• Prerequisites for Endor Labs MCP server
• Interactive setup through Gemini CLI
• Tools in the Endor Labs MCP server
• Choose your edition
• Developer Edition
• Enterprise Edition
• Scope options
• Manage MCP servers
• Configure GEMINI.md
• Install the MCP server as a Gemini extension
• Troubleshooting

Prerequisites for Endor Labs MCP server

Ensure that the following prerequisites are met:

• Gemini CLI
• Node.js version 18 or later (required if you don’t have endorctl installed)

Interactive setup through Gemini CLI

Select your edition, fill in any required fields, and click Copy to get the command that adds the Endor Labs MCP server to Gemini CLI.

Tools in the Endor Labs MCP server

Choose your edition

The Endor Labs MCP server has two editions:

• Developer Edition: A free edition that requires no configuration. A browser window opens on first use for authentication via GitHub, GitLab, or Google. The Developer Edition provides access to default security policies from Endor Labs.
• Enterprise Edition: A paid edition that enforces your organization’s specific security policies. Authenticate using GitHub, GitLab, Google, or SSO. You must specify your namespace to access your organization’s policies.

Additionally, if you already have Endor Labs configured locally (for example, from a previous endorctl init command), the MCP server can use your pre-existing configuration.

Developer Edition

Developer Edition: Add the MCP server with a single command

Run the following command to add the MCP server to your project. This adds the server with -s project (shared with everyone in the project). See Scope options for other scopes.

gemini mcp add endor-cli-tools -- npx -y endorctl ai-tools mcp-server

Developer Edition: Add the MCP server with settings.json configuration

Add the following to your .gemini/settings.json file in the root of your repository. This uses project scope, which is shared with everyone working on the repository.

{
  "mcpServers": {
    "endor-cli-tools": {
      "command": "npx",
      "args": [
        "-y",
        "endorctl",
        "ai-tools",
        "mcp-server"
      ]
    }
  }
}

Developer Edition: Verify the installation

/mcp list

Confirm that endor-cli-tools appears in the list. You can also use /mcp in Gemini CLI to view active MCP servers.

Try a test prompt

After installing the MCP server, try the following prompt in your AI chat or CLI to verify that the tools are working.

Check if the npm package lodash version 4.17.20 has any vulnerabilities

The MCP server uses the check_dependency_for_vulnerabilities tool to check for known vulnerabilities and return the results. If you see a response with vulnerability details, the MCP server is working correctly.

Enterprise Edition

For Enterprise Edition, you need your organization’s Endor Labs namespace and an authentication method. Ensure that your developers have Read-Only permissions to Endor Labs. See Authorization policies for more details.

Use the interactive setup tool above to configure your organization’s namespace and authentication method, and set up the MCP server.

Enterprise Edition: Add the MCP server with a single command

gemini mcp add -s user \
  -e ENDOR_NAMESPACE=<namespace> \
  -e ENDOR_MCP_SERVER_AUTH_MODE=<google|github|gitlab|sso> \
  -e ENDOR_TOKEN=automatic \
  endor-cli-tools -- npx -y endorctl ai-tools mcp-server

If you want to use SSO authentication, you must also add ENDOR_MCP_SERVER_AUTH_TENANT to the environment variables.

gemini mcp add -s user \
  -e ENDOR_NAMESPACE=my-org \
  -e ENDOR_MCP_SERVER_AUTH_MODE=sso \
  -e ENDOR_MCP_SERVER_AUTH_TENANT=my-tenant \
  -e ENDOR_TOKEN=automatic \
  endor-cli-tools -- npx -y endorctl ai-tools mcp-server

For example, if your Endor Labs namespace is my-org and you want to use Google authentication, run the following command:

gemini mcp add -s user \
  -e ENDOR_NAMESPACE=my-org \
  -e ENDOR_MCP_SERVER_AUTH_MODE=google \
  -e ENDOR_TOKEN=automatic \
  endor-cli-tools -- npx -y endorctl ai-tools mcp-server

Enterprise Edition: Add the MCP server with settings.json configuration

Add the following to your ~/.gemini/settings.json file to add the MCP server at user scope.

{
  "mcpServers": {
    "endor-cli-tools": {
      "command": "npx",
      "args": [
        "-y",
        "endorctl",
        "ai-tools",
        "mcp-server"
      ],
      "env": {
        "ENDOR_NAMESPACE": "<namespace>",
        "ENDOR_MCP_SERVER_AUTH_MODE": "<google|github|gitlab|sso>",
        "ENDOR_TOKEN": "automatic"
      }
    }
  }
}

If you want to use SSO authentication, you must also add ENDOR_MCP_SERVER_AUTH_TENANT to the env section.

{
  "mcpServers": {
    "endor-cli-tools": {
      "command": "npx",
      "args": [
        "-y",
        "endorctl",
        "ai-tools",
        "mcp-server"
      ],
      "env": {
        "ENDOR_NAMESPACE": "<namespace>",
        "ENDOR_MCP_SERVER_AUTH_MODE": "sso",
        "ENDOR_MCP_SERVER_AUTH_TENANT": "<tenant>",
        "ENDOR_TOKEN": "automatic"
      }
    }
  }
}

Replace <namespace> with your Endor Labs namespace and choose your authentication mode.

Enterprise Edition: Verify the installation

/mcp list

Confirm that endor-cli-tools appears in the list. You can also use /mcp in Gemini CLI to view active MCP servers.

Try a test prompt

After installing the MCP server, try the following prompt in your AI chat or CLI to verify that the tools are working.

Check if the npm package lodash version 4.17.20 has any vulnerabilities

The MCP server uses the check_dependency_for_vulnerabilities tool to check for known vulnerabilities and return the results. If you see a response with vulnerability details, the MCP server is working correctly.

Scope options

Gemini CLI supports two MCP configuration scopes:

• -s project: Shared with everyone in the project via .gemini/settings.json file (default).
• -s user: Available to you across all projects via ~/.gemini/settings.json.

Manage MCP servers

/mcp list

In Gemini CLI, use /mcp to view and manage your active MCP servers.

Configure GEMINI.md

To enhance the MCP server integration, you can add instructions in GEMINI.md at the root of your repository. Gemini CLI reads GEMINI.md files to guide AI development with your project-specific instructions.

1. Navigate to the root of your repository.

2. Create or edit the GEMINI.md file in the root of your repository.

3. Add appropriate rules for your project. For example, you can add a rule to check if the code is free from vulnerabilities.

Example GEMINI.md instructions

You can use the following GEMINI.md instructions as a quick start for the Endor Labs MCP server. Modify the instructions to meet your specific organization’s needs. For more information, refer to the Gemini CLI documentation.

• SCA Rule Example
• Secrets Rule Example
• SAST Rule Example

# Software Composition Analysis (SCA) Rule (Endor Labs via MCP)

This project uses Endor Labs for automated dependency (SCA) scanning, integrated through the MCP server.

## Workflow

Every time a manifest or lockfile (package.json, requirements.txt, go.mod, pom.xml, etc.) is created or modified in any way, immediately do the following prior to performing your next task.

**Important**: Do not proceed after creating or modifying a manifest file without running this first.

- Run `endor-cli-tools` using the `check_dependency_for_vulnerabilities` tool via the MCP server.
- Provide the **ecosystem**, **dependency name**, and **version** always when making this tool call.
- If a vulnerability or error is identified:
  - Upgrade to the suggested safe version, or
  - Replace the dependency with a non-vulnerable alternative.
- Re-run the check using `endor-cli-tools` to confirm the issue is resolved.

## Notes
- All scans must be performed using the MCP server integration (`endor-cli-tools`). Do not invoke `endorctl` directly.

# Leaked Secrets Detection Rule (Endor Labs via MCP)

This project uses [Endor Labs](https://docs.endorlabs.com/) for automated security scanning, integrated through the MCP server.

## Workflow

Whenever a file is modified in the repository, and before the end of an agent session:

- Run `endor-cli-tools` using the `scan` tool via the MCP server to check for leaked secrets.
- If any secrets or errors are detected:
  - Remove the exposed secret or correct the error immediately.
  - Re-run the scan to verify the secret has been properly removed.
- Save scan results and remediation steps in a security log or as comments for audit purposes.

## Notes
- All scans must be performed using the MCP server integration (`endor-cli-tools`). Do not invoke `endorctl` directly.
- This scan must use the path of the directory from which the changed files are in. Use absolute paths.

# Static Application Security Testing (SAST) Rule (Endor Labs via MCP)

This project uses [Endor Labs](https://docs.endorlabs.com/) for automated SAST, integrated through the MCP server.

## Workflow

Whenever a file is modified in the repository, and before the end of an agent session:

- Run `endor-cli-tools` using the `scan` tool via the MCP server to perform SAST scans.
- If any vulnerabilities or errors are found:
  - Present the issues to the user.
  - Recommend and apply appropriate fixes (e.g., input sanitization, validation, escaping, secure APIs).
- Save scan results and remediation steps in a security log or as comments for audit purposes.

## Notes
- All scans must be performed using the MCP server integration (`endor-cli-tools`). Do not invoke `endorctl` directly.
- Do not invoke Opengrep directly.
- This scan must use the path of the directory from which the changed files are in. Use absolute paths.

Install the MCP server as a Gemini extension

As an alternative to the MCP server configuration, you can install the Endor Labs MCP server as a Gemini extension. You can find the extension on GitHub.

gemini extensions install https://github.com/endorlabs/gemini-extension.git

No additional configuration is required for Developer Edition. When you first use a tool, a browser window opens allowing you to authenticate with GitHub, GitLab, or Google.

For Enterprise Edition, use a natural language command in Gemini CLI to initiate an authentication flow with your organization’s namespace after installing the extension. For example:

Initialize Endor Labs with Google authentication using the command endorctl init --auth-mode=google

Troubleshooting

"command": "endorctl",
"args": ["ai-tools", "mcp-server"]

The Endor Labs MCP server integrates directly into Augment Code to scan your code as you write, catching security issues before they reach production.

The following sections walk you through setting up the Endor Labs MCP server:

• Prerequisites for Endor Labs MCP server
• Interactive setup
• Tools in the Endor Labs MCP server
• Choose your edition
• Developer Edition
• Enterprise Edition
• Manage MCP server tools
• Troubleshooting

Prerequisites for Endor Labs MCP server

Ensure that the following prerequisites are met:

• Augment Code extension installed in Visual Studio Code
• Node.js version 18 or later (required if you don’t have endorctl installed)
• Windows users: See Prerequisites for Endor Labs MCP server on Windows for additional instructions

Interactive setup

Use the interactive configuration tool to generate the JSON configuration for the MCP server. Select your edition, fill in any required fields, and click Generate. Then paste the JSON into Augment Code’s Import from JSON in the MCP settings.

Tools in the Endor Labs MCP server

Choose your edition

The Endor Labs MCP server has two editions:

• Developer Edition: A free edition that requires no configuration. A browser window opens on first use for authentication via GitHub, GitLab, or Google. The Developer Edition provides access to default security policies from Endor Labs.
• Enterprise Edition: A paid edition that enforces your organization’s specific security policies. Authenticate using GitHub, GitLab, Google, or SSO. You must specify your namespace to access your organization’s policies.

Additionally, if you already have Endor Labs configured locally (for example, from a previous endorctl init command), the MCP server can use your pre-existing configuration.

Developer Edition

You can use the interactive setup tool above or set up the MCP server manually.

Developer Edition: Import from JSON

1. Open the Augment Code extension in Visual Studio Code.

2. Click the Settings icon in the upper right of the Augment panel.

3. In the MCP section, click Import from JSON.

4. Paste the following configuration and click Save.

   {
     "mcpServers": {
       "endor-cli-tools": {
         "command": "npx",
         "args": [
           "-y",
           "endorctl",
           "ai-tools",
           "mcp-server"
         ]
       }
     }
   }
   

   If you already have a local Endor Labs configuration from a previous endorctl init, use the following configuration instead to reuse your existing credentials:

   {
     "mcpServers": {
       "endor-cli-tools": {
         "command": "npx",
         "args": [
           "-y",
           "endorctl",
           "ai-tools",
           "mcp-server"
         ],
         "env": {
           "ENDOR_TOKEN": "automatic"
         }
       }
     }
   }
   

Developer Edition: Use the settings panel

1. Open the Augment Code extension in Visual Studio Code.

2. Click the Settings icon in the upper right of the Augment panel.

3. In the MCP section, click + to add a new MCP server.

4. Fill in the following fields:

   • Name: endor-cli-tools
   • Command: npx -y endorctl ai-tools mcp-server

5. Click Save to add the server.

Developer Edition: Verify the installation

1. Open the Augment Code extension in Visual Studio Code.

2. Click the Settings icon and confirm that endor-cli-tools appears in the MCP section.

Try a test prompt

After installing the MCP server, try the following prompt in your AI chat or CLI to verify that the tools are working.

Check if the npm package lodash version 4.17.20 has any vulnerabilities

The MCP server uses the check_dependency_for_vulnerabilities tool to check for known vulnerabilities and return the results. If you see a response with vulnerability details, the MCP server is working correctly.

Enterprise Edition

For Enterprise Edition, you need your organization’s Endor Labs namespace and an authentication method. Ensure that your developers have Read-Only permissions to Endor Labs. See Authorization policies for more details.

You can use the interactive setup tool above or set up the MCP server manually.

Enterprise Edition: Import from JSON

1. Open the Augment Code extension in Visual Studio Code.

2. Click the Settings icon in the upper right of the Augment panel.

3. In the MCP section, click Import from JSON.

4. Paste the following configuration and click Save.

   {
     "mcpServers": {
       "endor-cli-tools": {
         "command": "npx",
         "args": [
           "-y",
           "endorctl",
           "ai-tools",
           "mcp-server"
         ],
         "env": {
           "ENDOR_NAMESPACE": "<namespace>",
           "ENDOR_MCP_SERVER_AUTH_MODE": "<google|github|gitlab|sso>",
           "ENDOR_TOKEN": "automatic"
         }
       }
     }
   }
   

   Replace <namespace> with your Endor Labs namespace and choose your authentication mode. If you choose sso, you must also add ENDOR_MCP_SERVER_AUTH_TENANT to the env section.

Enterprise Edition: Use the settings panel

1. Open the Augment Code extension in Visual Studio Code.

2. Click the Settings icon in the upper right of the Augment panel.

3. In the MCP section, click + to add a new MCP server.

4. Fill in the following fields:

   • Name: endor-cli-tools
   • Command: npx -y endorctl ai-tools mcp-server

5. In the Environment variables section, add:

   • ENDOR_NAMESPACE: Your Endor Labs namespace
   • ENDOR_MCP_SERVER_AUTH_MODE: Your authentication mode (google, github, gitlab, or sso)
   • ENDOR_TOKEN: automatic

6. If you chose sso as the authentication mode, also add:

   • ENDOR_MCP_SERVER_AUTH_TENANT: Your tenant name

7. Click Save to add the server.

Enterprise Edition: Verify the installation

1. Open the Augment Code extension in Visual Studio Code.

2. Click the Settings icon and confirm that endor-cli-tools appears in the MCP section.

Try a test prompt

After installing the MCP server, try the following prompt in your AI chat or CLI to verify that the tools are working.

Check if the npm package lodash version 4.17.20 has any vulnerabilities

The MCP server uses the check_dependency_for_vulnerabilities tool to check for known vulnerabilities and return the results. If you see a response with vulnerability details, the MCP server is working correctly.

Manage MCP server tools

1. Open the Augment Code extension in Visual Studio Code.

2. Click the Settings icon in the upper right of the Augment panel.

3. In the MCP section, click the … button next to endor-cli-tools.

4. Edit the configuration or remove the server as needed.

Watch how to use Endor Labs with Augment Code

Troubleshooting

"command": "endorctl",
"args": ["ai-tools", "mcp-server"]

Prerequisites for Endor Labs MCP server on Windows

npx --version

The Endor Labs MCP server integrates directly into IntelliJ IDEA to scan your code as you write, catching security issues before they reach production.

The following sections walk you through setting up the Endor Labs MCP server:

• Prerequisites for Endor Labs MCP server
• Interactive setup
• Tools in the Endor Labs MCP server
• Choose your edition
• Developer Edition
• Enterprise Edition
• Configure Copilot rules
• Troubleshooting

Prerequisites for Endor Labs MCP server

Ensure that the following prerequisites are met:

• IntelliJ IDEA version 2025.2 or later, with GitHub Copilot installed
• Node.js version 18 or later (required if you don’t have endorctl installed)
• Windows users: See Prerequisites for Endor Labs MCP server on Windows for additional instructions

Interactive setup

Use the interactive configuration tool to set up the MCP server. The tool supports both the Developer Edition and the Enterprise Edition. Select your edition from the dropdown, configure your settings, and follow the instructions.

Tools in the Endor Labs MCP server

Choose your edition

The Endor Labs MCP server has two editions:

• Developer Edition: A free edition that requires no configuration. A browser window opens on first use for authentication via GitHub, GitLab, or Google. The Developer Edition provides access to default security policies from Endor Labs.
• Enterprise Edition: A paid edition that enforces your organization’s specific security policies. Authenticate using GitHub, GitLab, Google, or SSO. You must specify your namespace to access your organization’s policies.

Additionally, if you already have Endor Labs configured locally (for example, from a previous endorctl init command), the MCP server can use your pre-existing configuration.

Developer Edition

You can use the interactive setup tool above or set up the MCP server manually.

Developer Edition: Manual installation

If you prefer to configure the MCP server manually:

1. Open GitHub Copilot Chat from the right sidebar.

2. Switch to Agent mode.

3. Click Configure Tools.

4. Select + Add More Tools… from the bottom left corner to open the mcp.json file.

5. Add the following configuration to the mcp.json file.

   {
     "servers": {
       "endor-cli-tools": {
         "command": "npx",
         "args": [
           "-y",
           "endorctl",
           "ai-tools",
           "mcp-server"
         ]
       }
     }
   }
   

6. Save and close the mcp.json.

7. Switch from Agent to Ask mode in the chat and then back to Agent mode to reload the MCP server.

Developer Edition: Verify the installation

1. In the GitHub Copilot Chat, switch to Agent mode.

2. Click Configure Tools and confirm that endor-cli-tools appears in the list.

Try a test prompt

After installing the MCP server, try the following prompt in your AI chat or CLI to verify that the tools are working.

Check if the npm package lodash version 4.17.20 has any vulnerabilities

The MCP server uses the check_dependency_for_vulnerabilities tool to check for known vulnerabilities and return the results. If you see a response with vulnerability details, the MCP server is working correctly.

Enterprise Edition

For Enterprise Edition, you need your organization’s Endor Labs namespace and an authentication method. Ensure that your developers have Read-Only permissions to Endor Labs. See Authorization policies for more details.

You can use the interactive setup tool above or set up the MCP server manually.

Enterprise Edition: Manual installation

1. Open GitHub Copilot Chat from the right sidebar.

2. Switch to Agent mode.

3. Click Configure Tools.

4. Select + Add More Tools… from the bottom left corner to open the mcp.json file.

5. Add the following configuration to the mcp.json file.

   {
     "servers": {
       "endor-cli-tools": {
         "command": "npx",
         "args": [
           "-y",
           "endorctl",
           "ai-tools",
           "mcp-server"
         ],
         "env": {
           "ENDOR_NAMESPACE": "<namespace>",
           "ENDOR_MCP_SERVER_AUTH_MODE": "<google|github|gitlab|sso>",
           "ENDOR_TOKEN": "automatic"
         }
       }
     }
   }
   

   Replace <namespace> with your Endor Labs namespace and choose your authentication mode. If you choose sso, you must also add ENDOR_MCP_SERVER_AUTH_TENANT to the env section.

   The following parameters are used to configure the MCP server. All parameters are optional. If no parameters are provided, the MCP server defaults to the Developer Edition with browser authentication.

   • ENDOR_MCP_SERVER_AUTH_MODE: (Optional) The authentication mode to use for the MCP server. You can use the following authentication modes: github, gitlab, google, sso. If you choose sso, you must add ENDOR_MCP_SERVER_AUTH_TENANT as an additional parameter. If not specified, the MCP server defaults to browser authentication for the Developer Edition.
   • ENDOR_NAMESPACE: (Optional) The namespace to use for the MCP server. Required for Enterprise Edition to access your organization’s specific policies. Not needed for Developer Edition.
   • ENDOR_TOKEN: (Optional) Set to automatic to reuse an existing local endorctl configuration. When set to automatic, the MCP server skips browser authentication and uses your stored credentials. Do not set this to any other value; the MCP server manages the token internally during authentication.
   • ENDOR_MCP_SERVER_AUTH_TENANT: (Optional) The tenant name for SSO authentication. Required when ENDOR_MCP_SERVER_AUTH_MODE is set to sso for Enterprise Edition access.

6. Save and close the mcp.json.

7. Switch from Agent to Ask mode in the chat and then back to Agent mode to reload the MCP server.

8. Click Configure Tools and select endor-cli-tools.

Enterprise Edition: Verify the installation

1. In the GitHub Copilot Chat, switch to Agent mode.

2. Click Configure Tools and confirm that endor-cli-tools appears in the list.

Try a test prompt

After installing the MCP server, try the following prompt in your AI chat or CLI to verify that the tools are working.

Check if the npm package lodash version 4.17.20 has any vulnerabilities

The MCP server uses the check_dependency_for_vulnerabilities tool to check for known vulnerabilities and return the results. If you see a response with vulnerability details, the MCP server is working correctly.

Configure Copilot rules

Set up Copilot rules in .github/instructions/*.md to use the Endor Labs MCP server throughout the development process. See Add repository custom instructions for GitHub Copilot for more details.

Example Copilot rules

Copilot instructions define the guidelines that Copilot should follow throughout the development process. The following examples demonstrate how to use the Endor Labs MCP server within Copilot rules.

• SCA Rule Example
• Secrets Rule Example
• SAST Rule Example

---
description: "Dependency vulnerability scanning using Endor Labs via MCP server integration"
applyTo: '**/package.json, **/package-lock.json, **/yarn.lock, **/pnpm-lock.yaml, **/requirements.txt, **/Pipfile, **/Pipfile.lock, **/pyproject.toml, **/poetry.lock, **/go.mod, **/go.sum, **/Cargo.toml, **/Cargo.lock, **/pom.xml, **/build.gradle, **/build.gradle.kts, **/gradle.lockfile, **/composer.json, **/composer.lock'

---

# Software Composition Analysis (SCA) Rule (Endor Labs via MCP)
This project uses Endor Labs for automated dependency (SCA) scanning, integrated through the MCP server as configured in `mcp.json`.

## Workflow

Every time a manifest or lockfile listed above is created or modified in any way immediately do the following prior to performing your next task.

**Important**: Do not proceed after creating or modifying a manifest file without running this first. Do not write any other code or continue with your existing prompt. This is top priority whenever a manifest file is created or updated.

- Run `endor-cli-tools` using the `check_dependency_for_vulnerabilities` tool via the MCP server.
- Provide the **ecosystem**, **dependency name**, and **version** always when making this tool call. Do not forget to provide a version.
- If a vulnerability or error is identified:
  - Upgrade to the suggested safe version, or
  - Replace the dependency with a non-vulnerable alternative.
  - The AI agent must attempt to automatically correct all detected errors and vulnerabilities before session completion.
- Re-run the check using `endor-cli-tools` to confirm the issue is resolved.
- If an error occurs in any MCP server tool call (such as missing required parameters like version, invalid arguments, or tool invocation failures):
  - The AI agent must review the error, determine the cause, and automatically correct the tool call or input parameters.
  - Re-attempt the tool call with the corrected parameters.
  - Continue this process until the tool call succeeds or it is determined that remediation is not possible, in which case the issue and reason must be reported.

## Notes
- All scans must be performed using the MCP server integration (`endor-cli-tools`) as configured in `mcp.json`. Do not invoke `endorctl` directly.
- For troubleshooting, ensure the MCP server is running and `endorctl` is installed and accessible in your environment.

This rule ensures that all dependency changes are evaluated for risk at the time of introduction, and that the project remains clean and secure after each coding session. The scan may be performed at the end of an agent session, provided all modifications are checked and remediated before session completion.

---
description: "Scan for leaked secrets on file modification using Endor Labs via MCP server integration"
applyTo: '**/*'

---

# Leaked Secrets Detection Rule (Endor Labs via MCP)
This project uses [Endor Labs](https://docs.endorlabs.com/) for automated security scanning, integrated through the MCP server as configured in `mcp.json`.

## Workflow
Whenever a file is modified in the repository, and before the end of an agent session:
- Run `endor-cli-tools` using the `scan` tool via the MCP server to check for leaked secrets.
- Ensure the scan includes all file types and respects `.gitignore` unless otherwise configured.
- If any secrets or errors are detected:
  - Remove the exposed secret or correct the error immediately.
  - The AI agent must attempt to automatically correct all detected secrets and errors before session completion.
  - Re-run the scan to verify the secret or error has been properly removed or resolved.
- If an error occurs in any MCP server tool call (such as missing required parameters like version, invalid arguments, or tool invocation failures):
  - The AI agent must review the error, determine the cause, and automatically correct the tool call or input parameters.
  - Re-attempt the tool call with the corrected parameters.
  - Continue this process until the tool call succeeds or it is determined that remediation is not possible, in which case the issue and reason must be reported.
- Save scan results and remediation steps in a security log or as comments for audit purposes.

## Notes
- All scans must be performed using the MCP server integration (`endor-cli-tools`) as configured in `mcp.json`. Do not invoke `endorctl` directly.
- For troubleshooting, ensure the MCP server is running and `endorctl` is installed and accessible in your environment.
- **Important**: This scan must use the path of the directory from which the changed files are in. Do not attempt to set the path directly to a file as it must be a directory. Use absolute paths like /Users/username/mcp-server-demo/backend rather than relative paths like 'backend'

This rule ensures no accidental credentials, tokens, API keys, or secrets are committed or remain in the project history. The scan may be performed at the end of an agent session, provided all modifications are checked and remediated before session completion.

---
description: "Static Application Security Testing (SAST) using Endor Labs via MCP server integration"
applyTo: '**/*.c, **/*.cpp, **/*.cc, **/*.cs, **/*.go, **/*.java, **/*.js, **/*.jsx, **/*.ts, **/*.tsx, **/*.py, **/*.php, **/*.rb, **/*.rs, **/*.kt, **/*.kts, **/*.scala, **/*.swift, **/*.dart, **/*.html, **/*.yaml, **/*.yml, **/*.json, **/*.xml, **/*.sh, **/*.bash, **/*.clj, **/*.cljs, **/*.ex, **/*.exs, **/*.lua'

---

# Static Application Security Testing (SAST) Rule (Endor Labs via MCP)

This project uses [Endor Labs](https://docs.endorlabs.com/) for automated SAST, integrated through the MCP server as configured in `mcp.json`.

## Workflow

Whenever a file is modified in the repository, and before the end of an agent session perform the following workflow:

- Run `endor-cli-tools` using the `scan` tool via the MCP server to perform SAST scans as described above.
- If any vulnerabilities or errors are found:
  - Present the issues to the user.
  - The AI agent must attempt to automatically correct all errors and vulnerabilities, including code errors, security issues, and best practice violations, before session completion.
  - Recommend and apply appropriate fixes (e.g., input sanitization, validation, escaping, secure APIs).
  - Continue scanning and correcting until all critical issues have been resolved or no further automated remediation is possible.
- If an error occurs in any MCP server tool call (such as missing required parameters like version, invalid arguments, or tool invocation failures):
  - The AI agent must review the error, determine the cause, and automatically correct the tool call or input parameters.
  - Re-attempt the tool call with the corrected parameters.
  - Continue this process until the tool call succeeds or it is determined that remediation is not possible, in which case the issue and reason must be reported.
- Save scan results and remediation steps in a security log or as comments for audit purposes.

## Notes
- All scans must be performed using the MCP server integration (`endor-cli-tools`) as configured in `mcp.json`. Do not invoke `endorctl` directly.
- For troubleshooting, ensure the MCP server is running and `endorctl` is installed and accessible in your environment.
- Do not invoke Opengrep directly.
- **Important**: This scan must use the path of the directory from which the changed files are in. Do not attempt to set the path directly to a file as it must be a directory. Use absolute paths like /Users/username/mcp-server-demo/backend rather than relative paths like 'backend'

This rule ensures all code changes are automatically reviewed and remediated for common security vulnerabilities and errors using `endor-cli-tools` and the MCP server, with Opengrep as the underlying engine.

Watch how to use Endor Labs with IntelliJ IDEA

Troubleshooting

"command": "endorctl",
"args": ["ai-tools", "mcp-server"]

Prerequisites for Endor Labs MCP server on Windows

npx --version

Endor Labs Skills are pre-built AI agent instructions that automate common security workflows using endorctl. Skills provide structured prompts that guide your AI coding assistant through tasks like installing and configuring endorctl, authenticating with identity providers, scanning repositories for vulnerabilities, checking dependencies for vulnerabilities, and running secrets and SAST scans.

Endor Labs Skills work with AI coding agents that support project-level instructions, such as Claude Code and Cursor, with support for more AI coding agents coming soon. Each skill defines a specific security workflow, including trigger commands, required context, and expected output format.

Available skills

The following skills are available for installation:

• endor-setup: Install, authenticate, and configure endorctl automatically. Then run security scans for vulnerabilities, secrets, and SAST directly from your AI coding agent with zero manual setup.

Choose your IDE or platform to get started

Endor Labs skills integrate directly into Cursor to guide the AI assistant with reusable security workflows, catching security issues before they reach production.

The following sections walk you through setting up Endor Labs skills in Cursor:

• Install skills (npx)
• Use skills with Cursor

Install skills (npx)

You need Node.js v18+ for this method. Run the following from your project root to install all Endor Labs skills. The skills package detects Cursor automatically and installs skills into .cursor/skills/.

npx skills add endorlabs/ai-plugins

Use skills with Cursor

• “Set up endorctl and authenticate with Endor Labs.”
• “Run endorctl scan for this repo”
• “Run endorctl quick scan for this repo”

Endor Labs skills integrate directly into Claude Code to guide the AI assistant with reusable security workflows, catching security issues before they reach production.

The following sections walk you through setting up Endor Labs skills in Claude Code:

• Install as Claude plugin (recommended)
• Install skills only (npx)
• Use skills with Claude Code

Install as Claude plugin (recommended)

Install the Endor Labs plugin from the Claude Code (Terminal) plugin marketplace. This is the recommended way to get the full plugin experience.

1. In Claude Code, run:

   /plugin marketplace add endorlabs/ai-plugins
   

2. Then run:

   /plugin install ai-plugins@endorlabs
   

Install skills only (npx)

You need Node.js v18+ for this method. From your project root, run the following to install only the skills (without the full plugin). The skills package detects Claude Code and installs skills into .claude/skills/. This method is only useful if you want skills alone.

npx skills add endorlabs/ai-plugins

Use skills with Claude Code

• “Set up endorctl and authenticate with Endor Labs.”
• “Run endorctl scan for this repo”
• “Run endorctl quick scan for this repo”

AI security code review provides automated code review capabilities using artificial intelligence to identify potential security issues in your codebase.

After you set up AI security code review, creating a pull request triggers an Endor Labs scan on the diff. Endor Labs sends the scan data to an AI model to produce a security analysis and generates a report.

You can view the report in the Endor Labs user interface. You can also enable pull request comments to get a comment on your GitHub pull request with the details of the AI security code review.

The following sections provide information on how to set up AI security code review, customize a scan profile, and view the AI security code review results.

Before you set up AI security code review, ensure that the following prerequisites are in place:

• An active Endor Labs subscription with Endor Code Pro license.
• Administrator access to your GitHub organization.
• Access to configure scan profiles and policies.
• Enable Code Segment Embeddings and LLM Processing in Data Privacy settings.

Enable Code Segment Embeddings and LLM Processing

Perform the following steps to enable code segment embeddings and LLM processing:

1. Select Settings from the left sidebar.

2. Select SYSTEM SETTINGS > Data Privacy.

   

3. Select Code Segment Embeddings and LLM Processing.

4. Click Save Data Privacy Settings.

Verify license and feature access

Perform the following steps to verify your license and feature access:

1. Select Settings > License from the left sidebar.
2. Verify that you have Security Review in Products and Features.

To set up AI security code review, you need to complete the following tasks:

• Ensure that the GitHub App is installed and configured properly. If you are using endorctl, skip this step and ensure that you have set up the environment variables required for the endorctl scan command.
• Configure a scan profile for AI security code review.
• Enable the security review finding policy.
• Configure an action policy if you want to get comments on your GitHub pull request with the details of the AI security code review.

GitHub App Configuration

Install the GitHub App if you don’t have it already. See GitHub App for more information.

Ensure that you enable the following settings:

• Pull Request Scans: Pull Request Scans allows Endor Labs to scan the pull requests. You must enable this setting so that AI security code review can proceed for a pull request.
• Pull Request Comments: Pull Request Comments allows Endor Labs to comment on a pull request in GitHub. This setting is optional, and you need to enable this setting if you want a comment on your GitHub pull request with the details of the AI security code review. In addition, you also need to select Pull Request Comments in your scan profile and set up an action policy.

Configure scan profile for AI security code review

Create a scan profile for AI security code review and configure the following options:

• Pull Request Scans: Mandatory. This setting allows Endor Labs to scan the pull requests.
• Pull Request Comments: Optional. This setting allows Endor Labs to comment on a pull request in GitHub.
• AI security code review Scans: Mandatory. This setting allows Endor Labs to scan the pull requests for AI security code review.
• Disable Code Summary: Optional. This setting allows you to disable the code summary for the AI security code review.
• Custom Prompt: Optional. You can enter a custom prompt to modify how AI security code review detects and categorizes security-related changes.

After you create the scan profile, assign the scan profile to the projects for which you want to set up AI security code review.

See Scan Profiles for more information on creating a scan profile.

Enable finding policy for AI security code review

Ensure that the Security Review policy is enabled under finding policies.

1. Select Policies & Rules from the left sidebar.
2. Select Finding Policies.
3. Search for Security Review and ensure that the policy is enabled.

Configure action policy for pull request comments

If you want to get comments on your GitHub pull requests, you need to set up an action policy.

1. Select Settings from the left sidebar.

2. Select Action Policies.

3. Click Create Action Policy.

4. Select Security Review as the Policy Template.

5. Choose the severity threshold to trigger the AI security code review.

   You can choose from the following severity thresholds:

   • Any
   • Low
   • Medium
   • High
   • Critical

6. Select Pull Request as the Branch Type.

7. Choose Enforce Policy as the action, and select Warn or Break the Build depending on your preference.

8. Configure include and exclude patterns for the policy.

9. Name the policy and provide a description.

10. Enter tags if required for the policy.

11. Click Create Action Policy to save the policy.

See Action Policies for more information on setting up an action policy.

You can use AI security code review with endorctl and GitHub environment variables without requiring the GitHub App. This approach allows you to integrate AI security code review into your local development workflows. You can use this approach only if you have GitHub as your source control management system.

Complete the following tasks to set up AI security code review with endorctl:

• Complete the prerequisites to use AI security code review with endorctl.
• Set up the environment variables required to run endorctl for AI security code review.
• Install and authenticate endorctl, build your project, and run a scan. Scanning the repository creates the project in Endor Labs that you can use to configure the scan profile.
• Configure a scan profile for AI security code review.
• Enable the security review finding policy.
• Configure an action policy if you want to get comments on your GitHub pull request with the details of the AI security code review.
• Run scans for AI security code review.
• View results of the AI security code review.

Prerequisites to use AI security code review with endorctl

Ensure that the following prerequisites are met before using AI security code review with endorctl:

• An active Endor Labs subscription with Endor Code Pro license.
• Access to configure scan profiles and policies
• Code Segment Embeddings and LLM Processing enabled in Data Privacy settings
• A GitHub token with appropriate permissions.

Enable Code Segment Embeddings and LLM Processing

Perform the following steps to enable code segment embeddings and LLM processing:

1. Select Settings from the left sidebar.

2. Select SYSTEM SETTINGS > Data Privacy.

   

3. Select Code Segment Embeddings and LLM Processing.

4. Click Save Data Privacy Settings.

Verify license and feature access

Perform the following steps to verify your license and feature access:

1. Select Settings > License from the left sidebar.
2. Verify that you have Security Review in Products and Features.

Set up environment variables

Configure the following environment variables for GitHub integration:

# Required: SCM token with repo access
export ENDOR_SCAN_SCM_TOKEN=<your-scm-token>

# Required: Endor Labs authentication
export ENDOR_API_CREDENTIALS_KEY=<your-api-key>
export ENDOR_API_CREDENTIALS_SECRET=<your-api-secret>
export ENDOR_NAMESPACE=<your-namespace>

Pull request scan with AI security code review

To scan a pull request with AI security code review, fetch the pull request branch locally and checkout the branch.

git fetch origin pull/<PR_NUMBER>/head:pr-<PR_NUMBER>
git checkout pr-<PR_NUMBER>

For example, to scan pull request 12, you need to run the following commands.

git fetch origin pull/12/head:pr-12
git checkout pr-12

After you have fetched and checked out the pull request branch, you can run the following command to scan the pull request with AI security code review.

endorctl scan \
  -n <namespace> \
  --pr \
  --security-review \
  --scm-pr-id <PR_NUMBER> \
  --scm-token $ENDOR_SCAN_SCM_TOKEN \
  --enable-pr-comments

The following table describes the flags used in the command.

You can view the AI security code review results in the Endor Labs UI. You can also enable PR comments to get a comment on your GitHub PR with the details of the AI security code review. If you use merge queues, Endor Labs provides security review for the PRs until they are added to the merge queue. Endor Labs does a final security review on the merged commit SHA to the default branch.

View AI security code review results in Endor Labs UI

1. Select Projects from the left sidebar.

2. Select the project for which you want to view the AI security code review results.

3. Select Security Review.

   

   You can view the AI security code review results for all the pull requests raised in the project. You can also search for a specific pull request and view the results.

   You can filter the results by the type of the security issues, the severity of the security issues, the author of the PR, the approvers, and the creation time of the PR. You can select advanced to enter a search query to filter the results.

   For example, you can filter the results to show only the critical security issues that are part of unmerged pull requests:

   (spec.level in ["SECURITY_REVIEW_LEVEL_CRITICAL"] and spec.repository_pull_request_spec.merged != true)

4. Click on a pull request to view the detailed report.

   

   The report appears in the right sidebar. You can view the security analysis of the PR and the list of security risks along with their severities.

   You can click links against the security analysis to go directly to the lines of code that has the security risk.

   You can also click the links to view the pull request and the specific commit that introduced the security risk.

5. Select the arrow next to a security risk to view the details of the security risk.

   

   You can view the analysis of the security risk, the code snippet associated with the risk, and the details of the pull request.

Security review GitHub pull request comment

If you configure the action policy to get comments on your GitHub pull requests, Endor Labs comments on the pull request with the security analysis.

AI security code review PR comments provide automated feedback directly in your GitHub pull requests when potential security issues are detected in your code changes. This feature helps developers identify and fix security vulnerabilities before code is merged into the main branch.

When you create or update a pull request, Endor Labs automatically scans the diff of the pull request. The scan data is sent to a private and secure AI model for security analysis. A comment is automatically posted to your PR with the analysis. You can review the findings and make necessary changes.

If no security issues are detected, you can see a comment indicating a clean security review.

Benefits of AI security code review PR comments

You can get the following benefits with AI security code review PR comments:

• Get security feedback without leaving your development workflow
• Identify issues before code review or merge
• Reduce the time between writing code and discovering security problems
• Receive specific recommendations for fixing security issues
• Understand the security implications of your code changes
• Learn about security best practices through real examples

Content of AI security code review PR comment

After the analysis is complete, Endor Labs posts a comment directly on your pull request with the following information:

• Summary: A summary of the code changes in the pull request along with the file name and location of the code changes.
• Security Changes: A list of security changes in the pull request along with the file names and location of the security changes.

The following example shows how an AI security code review PR comment appears in a GitHub pull request.

Summary of code changes

The AI security review provides a comprehensive summary of all code changes in your pull request.

The summary includes the following information:

• Detailed change analysis: What was modified, added, or removed in each file.
• File paths and line numbers: Exact locations of all changes.
• Technical implementation details: Specific functions, configurations, and changes made in the code.
• Impact assessment: Analysis of how changes affect the overall system.

The following example shows a summary of code changes for a pull request.

Security Changes

The AI security review analyzes your code changes across different security aspects and provides detailed findings for any security-relevant changes.

The following sections describe the security changes in more detail.

• Comment structure of security changes
• Severity levels
• Category icons for security changes

The following example shows a security changes for a pull request.

Comment structure of security changes

The comment structure is as follows:

• Security Changes Header: Numbered count of security changes found.
• Security Aspect Icons: Visual indicators and category icons for quick identification.
• Severity Level: Critical, High, Medium, or Low classification.
• Detailed Description: Comprehensive explanation of the security concern.
• Code References: Specific file paths and line numbers with clickable links.
• Justification Section: Detailed explanation of why the change poses a security risk.

Severity levels

The following severity levels are used to classify the security changes:

• 🔴 Critical: Immediate security threats (prompt injection vulnerabilities, authentication bypasses).
• 🟠 High: Significant security risks (API endpoint issues, access control problems).
• 🟡 Medium: Security concerns to address (PII data handling, dependency security, JWT implementation).
• 🟢 Low: Minor security issues or best practice violations.

Category icons for security changes

The following category icons are used to classify the security changes:

• 📦 Dependency: Dependency security, library vulnerabilities.
• 🤖 AI: AI model security, prompt injection risks.
• 🔒 Access Control: Authentication, authorization, session management.
• 🔌 API Endpoint: API security controls, rate limiting.
• 🗄️ Database: Query construction, data access controls.
• 🔐 Cryptographic: Encryption, hashing, key management, JWT implementation.
• 💳 Payment Processing: Financial data security, PCI compliance.
• 🧠 Memory Protection: Buffer overflows, memory leaks.
• 👤 PII Data Handling: PII handling, data classification, local storage security.
• 📝 Input Validation: Data sanitization, injection prevention.
• 🏗️ Infrastructure: Cloud resources, container security.
• 🚀 CI/CD: Build pipeline security, artifact integrity.
• ⚙️ Configuration: Secrets management, environment variables.
• 🌐 Network: Firewall rules, network segmentation.

Endor Labs provides AI-powered assistance to help you understand vulnerabilities, troubleshoot issues, and accelerate security triage.

Endor AI Chat

Use the Endor AI Chat to understand vulnerabilities and view recommended actions. It leverages AI to provide contextual explanations, guidance, and next steps for issues detected in your project. With AI-powered context, you can reduce time spent digging through raw data and accelerate triage and remediation.

Prerequisites

To start using Endor Ask AI chat, you must enable Code Segment Embeddings and LLM Processing in Data Privacy settings.

1. Select Settings from the left sidebar.
2. Select SYSTEM SETTINGS > Data Privacy.
3. Select Code Segment Embeddings and LLM Processing.
4. Click Save Data Privacy Settings.

Use cases

• Investigate vulnerabilities: Use the AI chat to simplify technical details and generate summaries.
• Summarize scan results: Analyze scans performed by endorctl over time.
• Understand vulnerabilities: Ask natural-language questions about vulnerabilities in the database.
• Understand packages: Get quick explanations for package resolution and reachability errors.

Example questions

• Summarize this finding.
• Is this vulnerability exploitable?
• How do I remediate this?
• Is this a true positive SAST finding?
• Which issues were introduced or resolved?
• Why is this considered high severity?

Data scope for AI responses

Endor Ask AI chat agents generate answers based solely on specific data available within the Endor Labs platform:

• Findings
• Scan results
• Vulnerabilities
• Package versions

If the requested information falls outside this scope, the AI may not be able to generate a response.