"Using Git with Python for Operations" 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 AI agents and sportsbooks to discover, evaluate, and monitor alternative sports leagues with tools for discovery, valuation, fingerprinting, and market data.

MCP-compatible server that gives AI agents access to alternative sports data across 30+ leagues — odds, events, probabilities, settlement, and futures for prediction markets, DFS platforms, and sportsbooks.

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 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.

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

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.

An HTTP broker that exposes Strava data and operations (activities, routes, segments, etc.) as MCP tools, allowing users to interact with their own Strava account via natural language using per-user OAuth2 authentication.

Manages sports video metadata with CRUD operations for game information, teams, scores, and statistics. Enables advanced search filtering by game type, teams, league, season, and date ranges through PostgreSQL integration.

Provides surf forecast data including swell height, period, direction, and wind conditions for any location worldwide using the Open-Meteo Marine API. It also includes tools to find the best day to surf and integrates with MCP clients via a Python server.

MCP server for RapidOddsAPI that provides bookmaker odds, live scores, arbitrage and value bets to AI assistants. It supports querying sports, odds, results, and betting opportunities with credit-based usage.

Provides access to the Statbotics API for FIRST Robotics Competition statistical data and predictions. Enables AI assistants and other MCP clients to retrieve FRC team EPA ratings, event predictions, and match analytics.

Interprets advanced hockey player cards to translate metrics into plain-language assessments, supporting player evaluation, claim verification, and player comparisons with deterministic rules.

Provides AI agents with direct access to KingsPlaybook's sports data including confirmed lineups, player projections, game lines, and pick history via native MCP tools.

Analyzes your Trackman golf data to diagnose weaknesses and generate personalized practice plans with drills and progress tracking, acting as a data-driven coach.

An MCP server for ECNL and ECRL youth soccer, providing schedules, standings, and RPI for both boys and girls.

Provides local MCP tools for fantasy football draft simulation, weekly lineup decisions, and configurable automation policies.