Pitstop 🏎️

Your one-stop shop for Formula 1 data and insights via the Model Context Protocol (MCP).

📋 Table of Contents

• Overview

• Quick Start

• Available Tools

  • Tools Reference Table

  • Tool Details

• Setup

• Usage Examples

• Development

• Testing

Overview

Pitstop is an MCP server that provides comprehensive Formula 1 data access through Claude Desktop. Built on top of the FastF1 library and RSS feeds, it offers:

✨ Features

• 📰 Latest F1 news from multiple trusted sources

• 🔄 Silly season & transfer rumors with smart filtering

• 🏁 Complete session data (practice, qualifying, race)

• 📊 Detailed telemetry & lap-by-lap analysis

• 🌤️ Session weather conditions

• 🚦 Race control messages & incidents

• ⚡ Fast caching for improved performance

• 🎯 Type-safe responses with Pydantic models

Quick Start

Prerequisites

• Python 3.13+

• uv package manager

Installation

Configure Claude Desktop

Windows: Edit %APPDATA%\Claude\claude_desktop_config.json

macOS: Edit ~/Library/Application Support/Claude/claude_desktop_config.json

Note: Adjust paths to match your installation location. Use double backslashes (\\) on Windows.

Restart Claude Desktop to activate the tools.

Available Tools

🎯 Composable & Generic Tools - Each tool is designed to handle multiple use cases with flexible parameters, reducing complexity and improving usability.

Tools Reference Table

All tools return Pydantic models in JSON-serializable format for consistent data exchange.

Tool Details

📰 News & Updates

get_f1_news

Get Formula 1 news with flexible filtering options - a single composable tool for all news needs.

Parameters:

• source (str, optional): News source - "formula1", "fia", "autosport", "the-race", "racefans", "planetf1", "motorsport", or "all" (default: "formula1")

• limit (int, optional): Max articles 1-50 (default: 10)

• category (str, optional): News category - "general", "transfers", "management", "contracts", "silly_season" (default: "general")

• driver (str, optional): Filter by driver name (works with transfers, contracts, silly_season)

• team (str, optional): Filter by team name (works with management, contracts, silly_season)

• year (int, optional): Filter by year (works with silly_season)

Returns: News articles with titles, links, dates, summaries, and sources. Filtered news includes relevance scores.

Example Prompts:

🏆 Championships

get_standings

Get F1 World Championship standings for drivers and constructors.

Parameters:

• year (int): Season year (1950+)

• round (int | str, optional): Round number or GP name (e.g., "Monaco", 10)

• type (str, optional): "driver" or "constructor" (default: both)

• driver_name (str, optional): Filter by driver name

• team_name (str, optional): Filter by team name

Returns: Championship standings with positions, points, wins, and nationality.

Example Prompts:

🏁 Session Data

get_session_details

Get comprehensive details of a specific F1 session.

Parameters:

• year (int): Season year (2018+)

• gp (str | int): Grand Prix name (e.g., "Monza", "Monaco") or round number

• session (str): Session type - "FP1", "FP2", "FP3", "Q", "S", "R"

• include_weather (bool, optional): Include weather data (default: True)

• include_fastest_lap (bool, optional): Include fastest lap (default: True)

Returns: Complete session details including results, weather, fastest lap, and session stats.

Example Prompts:

get_session_results

Get results/classification from a specific session.

Parameters:

• year (int): Season year (2018+)

• gp (str | int): Grand Prix name or round number

• session (str): Session type - "FP1", "FP2", "FP3", "Q", "S", "R"

Returns: Session results with positions, driver info, times, teams, and status.

Example Prompts:

get_laps

Get lap data from an F1 session with flexible filtering - a single composable tool for all lap queries.

Parameters:

• year (int): Season year (2018+)

• gp (str | int): Grand Prix name or round number

• session (str): Session type - "FP1", "FP2", "FP3", "Q", "S", "R"

• driver (str | int, optional): Driver identifier - 3-letter code or number (default: all drivers)

• lap_type (str, optional): "all" or "fastest" (default: "all")

Returns: Lap data with times, sectors, tire compounds, track status, and speed data.

Example Prompts:

get_session_drivers

Get list of drivers who participated in a session.

Parameters:

• year (int): Season year (2018+)

• gp (str | int): Grand Prix name or round number

• session (str): Session type

Returns: List of driver identifiers who participated.

Example Prompts:

get_tire_strategy

Get tire strategy and compound usage for a session.

Parameters:

• year (int): Season year (2018+)

• gp (str | int): Grand Prix name or round number

• session (str): Session type

• driver (str | int, optional): Driver identifier (if None, returns all drivers)

Returns: Tire data per lap including compound, tire life, and stint information.

Example Prompts:

📊 Telemetry

get_lap_telemetry

Get detailed telemetry data for a specific lap.

Parameters:

• year (int): Season year (2018+)

• gp (str | int): Grand Prix name or round number

• session (str): Session type

• driver (str | int): Driver identifier

• lap_number (int): Specific lap number

Returns: High-frequency telemetry including speed, throttle, brake, gear, RPM, and DRS.

Example Prompts:

compare_driver_telemetry

Compare telemetry data between two drivers.

Parameters:

• year (int): Season year (2018+)

• gp (str | int): Grand Prix name or round number

• session (str): Session type

• driver1 (str | int): First driver identifier

• driver2 (str | int): Second driver identifier

• lap1 (int, optional): Lap number for driver1 (uses fastest if None)

• lap2 (int, optional): Lap number for driver2 (uses fastest if None)

Returns: Tuple of telemetry DataFrames for side-by-side comparison.

Example Prompts:

🌤️ Weather

get_session_weather

Get weather data throughout a session.

Parameters:

• year (int): Season year (2018+)

• gp (str | int): Grand Prix name or round number

• session (str): Session type

Returns: Weather data including air/track temps, humidity, pressure, wind, and rainfall.

Example Prompts:

🚦 Race Control

get_race_control_messages

Get official race control messages for a session.

Parameters:

• year (int): Season year (2018+)

• gp (str | int): Grand Prix name or round number

• session (str): Session type

Returns: Race control messages including flags, safety car periods, investigations, and penalties.

Example Prompts:

Setup

1. Install Dependencies

This installs:

• FastF1 - Formula 1 data access

• feedparser - RSS feed parsing

• MCP - Model Context Protocol

• Pydantic - Data validation

• httpx - HTTP client

2. Configure Claude Desktop

Add the following to your Claude Desktop config:

Windows: %APPDATA%\Claude\claude_desktop_config.json

3. Restart Claude Desktop

Completely quit and restart Claude Desktop for changes to take effect.

Usage Examples

Once configured, you can use Pitstop through Claude Desktop with natural language:

News & Updates:

Session Analysis:

Telemetry & Performance:

Race Control:

Development

Run Locally

Test the server using the MCP CLI:

Testing

Each tool can be tested individually using its built-in test function. All tools include a if __name__ == "__main__" block for standalone testing.

Test Individual Tools

Quick Command-Line Tests

Cache Management

FastF1 caches data in cache/ for performance. To clear:

Troubleshooting

Import Errors:

• Run uv sync to install dependencies

• Verify Python 3.13+ is installed

Connection Issues:

• Check paths in Claude Desktop config are correct

• Ensure double backslashes on Windows

• Restart Claude Desktop after config changes

Data Issues:

• Clear cache if data seems corrupted

• Verify year is 2018+ for session data

• Check that Grand Prix names are spelled correctly

Contributing

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

License

MIT License - see LICENSE file for details.

Acknowledgments

• FastF1 - Excellent Formula 1 data library

• Model Context Protocol - MCP specification

• F1 community for open data support

Built with ❤️ for F1 fans and data enthusiasts