Fastf1 MCP Server

@Surya96t

Basic information

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

Fastf1 MCP Server 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"
      }
    }
  }
}

Fastf1 MCP Server tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

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.

Frequently asked questions

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.

Comments

More Developer Tools MCP servers

Machina

MCP server for Machina's x402-powered AI agent services. 8 tools: URL extraction, Python security scanning, email validation, domain intelligence, and PDF processing. Pay-per-call in USDC on Base — no subscriptions, no A

Termany

thinkany-ai

Agent-Native Terminal

174

Perfex CRM

themesic

Turn Perfex CRM into an AI-ready workspace. This MCP server exposes your full REST API to Claude, ChatGPT and any AI agent, so leads, invoices and tasks are one prompt away.

Modelglass

Modelglass turns "which model should I use?" into a lookup instead of a guess. Seven tools give your agent live pricing across image, language, video, and audio models. Sourced and versioned, not scraped once and forgott

Mcp-Warden

ermoluk

Local-first credential broker for MCP. AI coding agents (Claude Code, Cursor, Codex…) call APIs, SSH and databases through scoped presets; secrets stay in your OS keychain and never enter the agent's context.