Skip to main content

F1 MCP Server

A Model Context Protocol (MCP) server that provides comprehensive Formula 1 data and analytics for Claude Desktop integration.

Features

This server exposes 36+ tools for accessing F1 data:

Race Data

  • Race results and classifications
  • Sprint race results
  • Qualifying progression (Q1, Q2, Q3)
  • Grid vs finish comparisons
  • DNF lists and retirement reasons

Telemetry & Analysis

  • Speed trace comparisons between drivers
  • Gear shift visualizations
  • Brake and throttle analysis
  • RPM and engine data
  • DRS usage patterns

Timing & Laps

  • Fastest lap data with sector times
  • Lap-by-lap timing
  • Deleted laps (track limits)
  • Lap consistency statistics
  • Personal best laps

Strategy

  • Tire compound analysis
  • Stint breakdowns
  • Pit stop data and fastest stops
  • Starting tire choices
  • Strategy comparisons

Standings & History

  • Driver championship standings
  • Constructor standings
  • Historical race winners
  • Track records

Live Data

  • Live session status
  • Real-time positions
  • Live lap times
  • Live telemetry
  • Current weather conditions

Other

  • Team radio links
  • Race control messages
  • Track status (flags, safety car)
  • Weather data
  • Circuit information

Installation

Prerequisites

  • Python 3.10 or higher
  • Claude Desktop

Setup

  1. Clone this repository:
git clone https://github.com/drivenrajat/f1.git
cd f1
  1. Create a virtual environment:
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate
  1. Install dependencies:
pip install -e .

Configure Claude Desktop

Add this server to your Claude Desktop MCP configuration (~/Library/Application Support/Claude/claude_desktop_config.json on macOS):

{
  "mcpServers": {
    "f1": {
      "command": "python",
      "args": ["/path/to/f1/f1_server.py"]
    }
  }
}

Or if using uv:

{
  "mcpServers": {
    "f1": {
      "command": "uv",
      "args": ["run", "--directory", "/path/to/f1", "python", "f1_server.py"]
    }
  }
}

Usage

Once configured, you can ask Claude questions like:

  • "Show me the 2024 F1 calendar"
  • "Get the race results from Monaco 2024"
  • "Compare telemetry between Verstappen and Norris at Silverstone qualifying"
  • "What was Hamilton's tire strategy at Spa?"
  • "Show me the current driver standings"
  • "Get the fastest pit stops from the Italian GP"

Data Sources

  • FastF1: Historical telemetry, lap times, and session data
  • Ergast API: Championship standings and historical results
  • OpenF1 API: Team radio recordings

Caching

The server automatically caches FastF1 data in a cache directory to improve performance on repeated queries.

License

MIT License - see LICENSE for details.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Metadata

Release files for f1-mcp 0.1.3

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for f1-mcp 0.1.3
File Size Uploaded
f1_mcp-0.1.3.tar.gz 30.6 MB Details

Built distribution (wheel)

Table of built distributions (wheels) for f1-mcp 0.1.3
File Interpreter ABI Platform
f1_mcp-0.1.3-py3-none-any.whl Python 3 none any Details

Total release size: 61.3 MB

Release files / f1_mcp-0.1.3.tar.gz

Download URL f1_mcp-0.1.3.tar.gz
Size 30.6 MB
Tags Source
SHA-256 checksum
How to use checksums
1d9e2f2c93f4f3f3208945ae2d9caed87b24bddcd3d2c1ed2e7908b954f3babf
BLAKE2b-256 checksum
How to use checksums
1098159851b1d8af83ce500d9ceafeea2119c4406aeb9cff00c5e72ffb9d7f45
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.12.5

Release files / f1_mcp-0.1.3-py3-none-any.whl

Download URL f1_mcp-0.1.3-py3-none-any.whl
Size 30.8 MB
Tags Python 3
SHA-256 checksum
How to use checksums
d8b69ba01fc434bbe55864449f186d63c86705c43f539ef9f559fe1b9302c30b
BLAKE2b-256 checksum
How to use checksums
ec7b24829190ba677e0472708529ec43a2b3a75746f1e45e2202ffd73964b7c2
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.12.5

Release history Release notifications | RSS feed

This release

0.1.3 This release

2 release files

0.1.2

2 release files

0.1.1

2 release files

0.1.0

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page