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CrowdStrike Falcon

Organization
crowdstrike

Connect AI agents to CrowdStrike Falcon for automated security analysis and threat hunting

Publishercrowdstrike
Repositoryfalcon-mcp
LanguagePython
Forks
49
Stars
159
Available tools
0
Transport typestdio
Categories
LicenseMIT
Links
  • Connect tools to AI workflows

    CrowdStrike Falcon exposes MCP capabilities that can be used by compatible AI clients and agents.

  • 0 available tools

    Browse the callable actions below, including names and descriptions when provided by the server.

  • Ready-to-copy setup

    Use the installation snippets to configure this server in your preferred MCP client.

  • Open source signals

    159 stars and 49 forks from the linked repository.

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falcon-mcp

PyPI version PyPI - Python Version License: MIT Documentation

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 crowdstrike.github.io/falcon-mcp.

Modules

ModuleDescription
CoreBasic connectivity and system information
Cloud SecurityKubernetes containers, image vulnerabilities, and CSPM asset inventory
Custom IOACreate and manage Custom IOA behavioral detection rules and rule groups
DetectionsFind and analyze detections to understand malicious activity
DiscoverSearch application inventory and discover unmanaged assets
Firewall ManagementSearch and manage firewall rules and rule groups
HostsManage and query host/device information
Identity ProtectionEntity investigation and identity protection analysis
IntelResearch threat actors, IOCs, and intelligence reports
IOCSearch, create, and remove custom indicators of compromise
NGSIEMExecute CQL queries against Next-Gen SIEM
Real Time ResponseInitialize RTR sessions and execute read-only triage commands
Scheduled ReportsManage scheduled reports and download report files
Sensor UsageAccess and analyze sensor usage data
ServerlessSearch for vulnerabilities in serverless functions
ShieldSaaS security posture, checks, alerts, and app inventory
SpotlightManage and analyze vulnerability data and security assessments

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

Quick Start

Install

Using uv (recommended)

bash
uv tool install falcon-mcp

Using pip

bash
pip install falcon-mcp

Configure

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

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

Run

bash
falcon-mcp

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

Editor Integration

Using uvx (recommended)

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

With Module Selection

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

Docker

json
{
  "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

bash
# 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.

Deployment Options

Contributing

bash
# 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

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 CrowdStroke 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.

Installation

TypingMind
Prerequisites:

Node.js 18+

{
  "mcpServers": {
    "falcon-mcp": {
      "command": "uvx",
      "args": [
        "falcon-mcp"
      ],
      "env": {
        "FALCON_CLIENT_ID": "your-client-id",
        "FALCON_CLIENT_SECRET": "your-client-secret",
        "FALCON_BASE_URL": "https://api.crowdstrike.com"
      }
    }
  }
}

Use CrowdStrike Falcon MCP with multiple AI models

TypingMind connects MCP tools at the workspace level, so once CrowdStrike Falcon is connected, you can use it with different AI models in TypingMind instead of setting it up separately for each model. This MCP runs locally through the TypingMind MCP connector on your device.

Setup guide to use the local connector

Use this when the MCP server needs access to local files, apps, or private resources on your computer.

1

Open the MCP settings

In TypingMind, go to Settings, Advanced Settings, then Model Context Protocol and choose Setup Connector.

  1. Open TypingMind in your browser.
  2. Click the Settings icon.
  3. Go to Advanced Settings.
  4. Open the Model Context Protocol section.
  5. Click Setup Connector and choose This Device.
TypingMind MCP connector setup screen with This Device selected
2

Run the connector command

Choose This Device, copy the command from TypingMind, and run it in Terminal. Keep the process running while you use MCP.

  1. Copy the setup command shown by TypingMind.
  2. Open Terminal on macOS or Windows Terminal on Windows.
  3. Paste and run the command.
  4. Approve the package install if Terminal asks you to proceed.
  5. Keep the Terminal window running while using MCP tools.
3

Add CrowdStrike Falcon as a server

When the connector status is Ready, click Edit Servers and paste the MCP server configuration.

  1. Wait until the connector status shows Ready.
  2. Click Edit Servers.
  3. Paste the CrowdStrike Falcon MCP server configuration.
  4. Save the server list.
  5. Refresh if you want to confirm the connector is still ready.
TypingMind MCP settings showing active server and Edit Servers button
{
  "mcpServers": {
    "crowdstrike-falcon": {
      "command": "npx",
      "args": [
        "-y",
        "falcon-mcp"
      ]
    }
  }
}
4

Use it across models

Save the server list, open Plugins, enable the CrowdStrike Falcon MCP tools, then select any supported AI model in TypingMind and use the tools in chat or assign them to an AI agent.

  1. Open the Plugins page in TypingMind.
  2. Enable the CrowdStrike Falcon MCP tools.
  3. Start a chat and choose the AI model you want to use.
  4. Use the MCP tools in chat or assign them to an AI agent.
  5. Switch to another AI model whenever needed without reconnecting MCP.
TypingMind chat using enabled MCP tools with a selected AI model
Can you use CrowdStrike Falcon to help me with this task?
CrowdStrike Falcon
Sure. I read it.
Here is what I found using CrowdStrike Falcon.

Frequently asked questions

What is the CrowdStrike Falcon MCP server used for?

CrowdStrike Falcon is an MCP server that lets compatible AI clients connect to external tools and context. In TypingMind, you can add this MCP server once and make its tools available in your AI workspace.

Can I use CrowdStrike Falcon MCP with multiple AI models in TypingMind?

Yes. TypingMind connects MCP tools at the workspace level, so you can use CrowdStrike Falcon with different AI models such as Claude, ChatGPT, Gemini, or other models you have configured in TypingMind without setting up the MCP server separately for each model.

Why use CrowdStrike Falcon MCP with TypingMind?

TypingMind is one of the best frontends for LLM chat because it brings multiple AI models, prompts, plugins, AI agents, API keys, and MCP tools into one workspace. With CrowdStrike Falcon connected, you can use its MCP tools across your preferred models while keeping your chat workflow organized in TypingMind.

How do I connect CrowdStrike Falcon MCP to TypingMind?

CrowdStrike Falcon runs through the TypingMind local MCP connector. This is best when the MCP server needs access to local files, desktop apps, command-line tools, or private resources on your computer.

What tools does CrowdStrike Falcon MCP provide in TypingMind?

CrowdStrike Falcon exposes MCP capabilities that can be enabled from the TypingMind Plugins page and used in chat or assigned to AI agents.

Do I need to share my API keys with TypingMind to use CrowdStrike Falcon MCP?

No. TypingMind is local-first and lets you keep your model providers, API keys, prompts, and MCP configuration under your control. If CrowdStrike Falcon requires authentication, add the required headers, OAuth settings, or local configuration for that MCP server when you create the connection.

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