"Python Object-Oriented Programming Resources" 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.

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.

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

Provides live Fantasy Premier League data, expected-goals analytics, and a linear-programming squad optimizer, enabling users to build optimal FPL squads, compare players, find value picks, and get transfer and captain advice through natural language.

MCP server for NFL fantasy football retrieval, providing access to NFL stats and Sleeper league data through retrieval-oriented tools.

Provides read-only access to the Handigraphs Stats API v1, enabling discovery of sports resources and querying of protected sports statistics.

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.

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 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.

Enables AI agents to query live and historical sports analytics, consensus betting odds, predictions, scores, schedules, standings, rosters, news, play-by-play, and win probabilities through structured tools and resources.

Enables natural-language access to Chess.com's public API, exposing player, club, tournament, puzzle, and leaderboard data through tools and resources without authentication.

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.

Provides tools and resources to interact with the Fantasy Premier League API, enabling player analysis, fixture insights, and team management through natural language.

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.