"A system or platform with knowledge of all Python packages" matching MCP servers:

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

Enables natural language querying of a football knowledge graph via Neo4j, generating Cypher queries and answers using LLMs, and also provides tools to build the graph from text.

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.

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.

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 Claude, ChatGPT and other MCP clients to look up members, their memberships and credentials, events and event bookings, and clubs and other organisations in a sports membership platform, and, when writes are enabled, to change the dates of a member's membership.

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.

Enables AI agents to safely interact with golf course operations by providing real-time inventory, booking rules, pricing policies, and a self-learning memory system.

Converts Claude Desktop into a sports content production studio, enabling search of football transfer tweets and generation of complete videos with virtual presenters.

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 tools to query sports tournaments, leaderboards, predictions, and match stats from the Tulidu Sport platform.

Enables interaction with the CopaMind platform via MCP, exposing read-only and write tools for querying match predictions, Monte Carlo simulations, team rankings, and RAG-based explanations, all while maintaining full traceability and reproducibility.

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.

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.

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

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.

Read-only MCP server for the PlayMetrics youth-sports club management platform, enabling AI agents to query clubs, teams, players, schedules, registrations, and payments.

Enables natural-language querying of historical NBA game data from a read-only SQLite database.