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Fastf1 Mcp Server

@Surya96t

Repository

About Fastf1 Mcp Server

MCP server for Formula 1 data via the FastF1 library. Ask Claude (or any MCP-compatible client) about race results, lap times, telemetry, standings, pit stops, and qualifying — with historical data back to 1950 via the Ergast API.

#formula1#f1#fastf1#telemetry#motorsport#mcp#sports#data#ergast#claude

Basic information

Category

Developer Tools

Transports

stdio

Publisher

Surya96t

Submitted by

Surya Prakash

Config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "fastf1": {
      "command": "uv",
      "args": [
        "run",
        "fastf1-mcp-server"
      ],
      "cwd": "/absolute/path/to/fastf1-mcp",
      "env": {
        "FASTF1_MCP_LOG_LEVEL": "INFO",
        "FASTF1_MCP_MAX_CACHED_SESSIONS": "10"
      }
    }
  }
}

Tools

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Overview

What is Fastf1 Mcp Server?

Fastf1 Mcp Server is an MCP server that exposes Formula 1 data to AI assistants via the FastF1 library. It provides 21 tools, 4 resources, and 5 prompts for querying race results, lap times, telemetry, standings, and more.

How to use Fastf1 Mcp Server?

Install with uv or pip, configure via environment variables, then run the server directly or add it to your MCP client configuration (e.g., Claude Desktop's claude_desktop_config.json). The server runs locally and communicates over stdio.

Key features of Fastf1 Mcp Server

  • 21 tools covering standings, results, telemetry, and strategy.
  • 4 MCP resources for schedule, driver, constructor, and circuit data.
  • 5 guided prompts for race recaps and analysis.
  • Async-safe LRU session cache for fast repeat queries.
  • Automatic telemetry sampling to ≤ 500 data points.

Use cases of Fastf1 Mcp Server

  • Ask an AI assistant for a full race recap including strategy.
  • Compare telemetry between two drivers in a qualifying session.
  • Analyze who had the fastest theoretical lap in a session.
  • Look up constructor or driver standings at any point in a season.

FAQ from Fastf1 Mcp Server

What data sources does the server use?

It uses the Ergast API (1950–present) for historical data and FastF1 Live Timing (2018–present) for session data.

What are the runtime requirements?

Python 3.12+ and either uv (recommended) or pip for installation.

How does telemetry sampling work?

Telemetry data is sampled to a maximum of 500 points (default 200) to manage large raw datasets.

How is caching handled?

An LRU in-memory cache stores up to 10 sessions by default, configurable via FASTF1_MCP_MAX_CACHED_SESSIONS. A disk cache path is also configurable.

What authentication or transport is required?

No authentication is needed. The server runs locally via stdio transport and can be tested with the MCP Inspector.

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