"A tool for analyzing Python repository structure and code relationships" matching MCP servers:

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.

Enables MCP clients to fetch live football odds and team form, and flag matches where the market price diverges from a simple form-based estimate.

Standalone Model Context Protocol server for PropProfessor, plus a small query CLI for local analysis.

Provides access to live NHL game data, team and player statistics, standings, schedules, playoff information, and head-to-head comparisons through natural language queries using official NHL APIs.

Provides a tool to retrieve today's 2026 FIFA World Cup matches, including teams, time, venue, and scores.

Connects Claude to Lichess for playing chess games, analyzing positions with Stockfish cloud evaluation, and solving puzzles. Supports real-time gameplay including moves, challenges, draw offers, and accessing user profiles and game history.

Enables querying and analyzing sports activities from Strava and Garmin Connect, including sleep and recovery data.

Manages Fantasy Premier League teams via natural language, reading team data, analyzing players and fixtures, and executing actions like transfers, captain changes, and chips.

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.

A Python MCP server providing 11 tools for querying KenPom basketball analytics, including efficiency ratings, game predictions, four factors, and more through Claude.

A minimal Python MCP server that provides surf forecasts for a single Surfline spot. It fetches both conditions and rating data through the get_surf_forecast tool.

A Python-based MCP server that extracts football match data from multiple global sources like ESPN and BBC Sport using intelligent web scraping. It enables AI assistants to retrieve scheduled matches, real-time scores, and broadcasting details with advanced filtering for high-profile games.

Enables fast real-time web search and access to premium data from trusted sources including news, financial markets, sports, and more. Supports AI agents with live data and curated content from various domains.

Answers lineup, trade, waiver, and playoff-odds questions by running deterministic Python analysis and returning conclusions, not raw data.

MCP server for analyzing running data from Intervals.icu, offering tools for athlete profiles, activity details, fitness trends, and running summaries.

MCP server for managing tennis club member data from local CSV/Excel exports. Provides tools for searching, filtering, and analyzing member information.

Enables analyzing Codeforces activity through local MCP tools, including weekly practice summaries, problem recommendations, user comparisons, weak-topic detection, contest tracking, and rating progress.

Enables fetching upcoming events for London Desperados CC from Spond via a single tool, get_desperados_events.

Exposes a single tool for Claude to fetch recent Strava activities, including detailed metrics and lap breakdowns, for automatic training summaries.

An MCP server that enables natural language querying of over 10 million ball-by-ball cricket deliveries stored in a local DuckDB database. It provides 26 tools for analyzing player matchups, situational stats, and historical records across all major cricket formats and tournaments.