"A tool or library for executing Python code" 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.

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.

An MCP server for Fantasy Premier League that allows querying gameweek info, player recommendations, squad management, and executing transfers via FPL's public API with optional cookie authentication.

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.

Enables AI agents to query real-time and historical Formula 1 data, including Grand Prix meetings, sessions (races, qualifying, practice), drivers, and lap times or telemetry, with support for filtering by year, country, session, and driver. Can be used via the Pipeworx gateway or as a local stdio server.

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.

Enables AI agents to query sports data including teams, players, events, and standings from TheSportsDB through natural language or direct tool calls.

Read-only MCP server for reviewing completed public Lichess games, providing tools to fetch a game or list recent completed games with strict safety and cost boundaries.

Wraps CricAPI to provide live cricket data, enabling AI agents to query cricket information through natural language or direct tool calls.

Enables querying community-run, keyless football/soccer match data from OpenLigaDB through natural language or direct tool calls.

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.

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