f1

This MCP server exposes Formula One data and statistics via the FastF1 Python library through a Node-based MCP interface. It allows you to fetch race calendars, event details, session results, driver information, lap times, telemetry, and championship standings using the provided tools. The server is designed to be queried through the MCP gateway so you can compose natural language or structured requests to retrieve specific data for a given year, event, and session. Tools include get_event_schedule, get_event_info, get_session_results, get_driver_info, analyze_driver_performance, compare_drivers, get_telemetry, and get_championship_standings, enabling both individual data lookups and comparative analyses across drivers or sessions.

Prerequisites:

• Node.js 18 or later
• Python 3.8 or later
• Git (optional, for cloning)

Install Python dependencies (FastF1 and data libraries):

pip install fastf1 pandas numpy

Install Node.js dependencies for the MCP server:

cd f1-mcp-server
npm install

Build the TypeScript server (if applicable):

npm run build

Add the MCP server to your MCP settings (example snippet):

{
  "mcpServers": {
    "formula1": {
      "command": "node",
      "args": ["/path/to/your/project/build/index.js"],
      "disabled": false,
      "autoApprove": []
    }
  }
}

Notes:

• Ensure Python and FastF1 are installed and accessible to the MCP process. If your environment requires a virtual environment, activate it before starting the MCP server.
• The server relies on FastF1 for data access; internet access and correct data source permissions are required.
• Update the command path in mcp_config to point to your built index.js location after building.
• If you use a different path or container environment, adjust the executable path accordingly in the MCP settings.
• Environment variables like PYTHONPATH or FASTF1_CONFIG can be added to env in mcp_config if needed by your runtime environment.