Falcon MCP Server

falcon-mcp

falcon-mcp is a Model Context Protocol (MCP) server that connects AI agents with the CrowdStrike Falcon platform, powering intelligent security analysis in your agentic workflows. It delivers programmatic access to essential security capabilities—including detections, threat intelligence, and host management—establishing the foundation for advanced security operations and automation.

[!IMPORTANT] 🚧 Public Preview: This project is currently in public preview and under active development. Features and functionality may change before the stable 1.0 release. While we encourage exploration and testing, please avoid production deployments. We welcome your feedback through GitHub Issues to help shape the final release.

Documentation

Full docs are available at developer.crowdstrike.com/falcon-mcp.

Modules

See the Module Overview for required API scopes, available tools, and FQL resources.

Quick Start

Install

Using uv (recommended)

uv tool install falcon-mcp

Using pip

pip install falcon-mcp

Configure

Set the required environment variables (or use a .env file — see the Configuration Guide):

export FALCON_CLIENT_ID="your-client-id"
export FALCON_CLIENT_SECRET="your-client-secret"
export FALCON_BASE_URL="https://api.crowdstrike.com"

Run

falcon-mcp

See the Getting Started guide for full installation and configuration details.

Editor Integration

Using uvx (recommended)

{
  "mcpServers": {
    "falcon-mcp": {
      "command": "uvx",
      "args": [
        "--env-file",
        "/path/to/.env",
        "falcon-mcp"
      ]
    }
  }
}

With Module Selection

{
  "mcpServers": {
    "falcon-mcp": {
      "command": "uvx",
      "args": [
        "--env-file",
        "/path/to/.env",
        "falcon-mcp",
        "--modules",
        "detections,hosts,intel"
      ]
    }
  }
}

Docker

{
  "mcpServers": {
    "falcon-mcp-docker": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "--env-file",
        "/full/path/to/.env",
        "quay.io/crowdstrike/falcon-mcp:latest"
      ]
    }
  }
}

See the Usage guide for all command line options, module configuration, and library usage.

Container Usage

# Pull the latest image
docker pull quay.io/crowdstrike/falcon-mcp:latest

# Run with .env file (stdio transport)
docker run -i --rm --env-file /path/to/.env quay.io/crowdstrike/falcon-mcp:latest

# Run with streamable-http transport
docker run --rm -p 8000:8000 --env-file /path/to/.env \
  quay.io/crowdstrike/falcon-mcp:latest --transport streamable-http --host 0.0.0.0

See the Docker Deployment guide for building locally, custom ports, and advanced configurations.

Dynamic Mode

Running many modules at once inflates the context window every AI client must hold. Dynamic mode replaces the full tool surface with three tools — falcon_list_enabled_modules to see which modules are loaded, falcon_search_tools to discover the right tool on demand, and falcon_execute_tool to run it — so agents only load the schemas they actually need.

falcon-mcp --dynamic
# or: FALCON_MCP_DYNAMIC=true

See the Dynamic Mode guide for the full discover → execute workflow and trade-offs.

Deployment Options

• Amazon Bedrock AgentCore
• Google Cloud (Cloud Run / Vertex AI)

Contributing

# Clone and install
git clone https://github.com/CrowdStrike/falcon-mcp.git
cd falcon-mcp
uv sync --all-extras

# Run tests
uv run pytest

[!IMPORTANT] This project uses Conventional Commits for automated releases. Please follow the commit message format outlined in our Contributing Guide.

Developer Documentation

• Documentation Guide: Architecture and maintenance guide for the documentation
• Module Development Guide: Instructions for implementing new modules
• Resource Development Guide: Instructions for implementing resources
• End-to-End Testing Guide: Guide for running and understanding E2E tests
• Integration Testing Guide: Guide for running integration tests with real API calls

License

This project is licensed under the MIT License - see the LICENSE file for details.

Support

This is a community-driven, open source project. While it is not an official CrowdStrike product, it is actively maintained by CrowdStrike and supported in collaboration with the open source developer community.

For more information, please see our SUPPORT file.