"Comparison of Python-based tools for converting TeX to Lean" 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 to discover live and recent football matches, scores, and fan clips on Vublox. Supports searching by team, league, or keyword and retrieving match summaries.

Provides real-time access to League of Legends esports data including live matches, schedules, leagues, event details, and VODs through a standardized interface.

An MCP Server that provides access to League of Legends statistics via the SportData.io API, allowing agents to query and analyze LoL competitive gaming data.

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.

Enables natural-language querying of a local DuckDB warehouse of NFL play-by-play data, converting questions into SQL and returning results.

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.

An MCP server that exposes sports-data APIs from multiple providers (AFL, Sportsbet, Entain, NRL) as interchangeable tools, enabling cross-provider odds and stats comparison.

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 chess position analysis, legal move investigation, move comparison, and PGN game reconstruction through MCP tools.

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.

Provides access to a cited knowledge graph on football's Laws of the Game and major competitions, with tools for search, question answering, and entity exploration, returning claims with sources and confidence.

Enables natural language querying of Feyenoord football match data, converting questions to SQL queries and returning results.

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

Enables access to and analysis of a curated historical football database covering 37,000 matches across European competitions, with tools for team/player search, match details, form, head-to-head, comparisons, and match prediction.

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.

MCP server providing Claude live access to USL Super League data—teams, matches, standings, rosters, and schedule-strength analytics—via the ESPN public API.