"F-Droid" matching MCP servers:

Exposes the canonical 7-0 knowledge surface — game modes, roster picks, and scenarios, FAQ, official links

Provides live Formula 1 data such as driver standings, race results, and schedule for the current season, enabling users to ask about F1 without stale training data.

Provides comprehensive Formula 1 data and analytics for Claude Desktop, including race results, telemetry, standings, and strategy insights through 36+ tools.

Exposes Formula 1 historical data (race results, qualifying, pit stops, and championship standings) as callable tools for LLMs via the Jolpica-F1 API.

Enables querying K League official data (rankings, matches, players) via SQL using natural language, with a pre-built SQLite database.

A real-time Formula 1 analytics server that lets you ask natural language questions about races, lap times, tyre strategies, pit stops, and more using live data from the OpenF1 API.

29 MCP tools for IPL 2026, IPL historical (18 seasons), and Major League Cricket. Free, no API key.

Exposes the 82-0 Dream NBA lineup game's game modes, roster picks, scenarios, FAQ, and official links to MCP-compatible AI clients.

MCP server providing access to ESPN Fantasy Baseball data, enabling league settings, rosters, player lookup, free agents, waiver claims, lineup changes, and trade management.

Provides verified game rules, official links, and FAQ for the 17-0 NFL roster strategy game to MCP-compatible AI clients.

Provides game rules, roster constraints, FAQ, and official links for the 27-0 NRL fantasy draft game, enabling AI clients to retrieve this knowledge.

Provides professional cycling data from FirstCycling, allowing users to retrieve comprehensive information about cyclists, race results, historical cycling data, and team information through natural language queries.

Enables AI assistants to read and analyze athlete training data, including fitness summaries, activities, and profiles, to help plan training.

Exposes the canonical 17-0 knowledge surface including game rules, roster constraints, and entry points for the NFL roster strategy game to MCP-compatible AI clients.

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.

Gives AI assistants structured access to racing-game telemetry such as lap and sector times, lap comparisons, braking zones and tyre wear through MCP tools and resources. It works out of the box on bundled synthetic sample data and can ingest a live F1 23 UDP feed.

Formula 1 data from the OpenF1 API: sessions, standings, laps, telemetry, and race replay.

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.

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.

Provides comprehensive Formula 1 data access including race schedules, session results, lap times, telemetry data, driver/constructor standings, and circuit information. Enables users to retrieve and analyze F1 racing data through natural language queries using the FastF1 Python package.