"Testing Library" matching MCP servers:

Provides access to comprehensive MLB baseball statistics through the MLB Stats API, pybaseball library, Statcast data, FanGraphs, and Baseball Reference, including support for generating matplotlib visualizations.

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.

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.

Connects AI assistants to any TrainingPeaks account via secure cookie authentication (no API approval needed) to query workouts, fitness trends (CTL/ATL/TSB), power PRs, health metrics, equipment, events and training plans through natural language. Also enables creating and scheduling structured interval, strength and library workouts, updating zones and FTP, and managing calendars and athlete groups.