Provides Formula One data and statistics through a Model Context Protocol interface, allowing users to access race calendars, session results, driver statistics, telemetry data, and championship standings.
A Model Context Protocol server that provides comprehensive Formula One racing data, enabling access to event schedules, driver information, telemetry data, race results, and performance analytics through natural language queries.
This project implements a Model Context Protocol (MCP) server providing Formula One racing data using the Python FastF1 library. Inspired by an existing TypeScript server, it offers similar F1 data functionalities natively in Python via FastF1.
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.
Enables access to Formula 1 data from the openF1.org API, including driver information, race results, lap times, telemetry, pit stops, weather conditions, and live position data across multiple seasons.
A local MCP server that gives Claude (or any MCP-compatible AI client) access to Formula 1 race data. Load any session from 2018 onwards, ask questions in natural language, and get answers backed by real telemetry, timing, and strategy data.