Python MCP server that provides comprehensive access to MLB statistics and baseball data through a FastAPI-based interface. Acts as a bridge between AI applications and MLB data sources, enabling seamless integration of baseball statistics, game information, player data, and more.
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 access to Chess.com player data, game records, and public information through standardized MCP interfaces, allowing AI assistants to search and analyze chess information.
Connect AI agents to OP.GG Esports data and retrieve upcoming League of Legends match schedules effortlessly. Access structured match information through a standardized interface, enhancing your AI's capabilities with real-time esports data.
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.
