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    Provides real-time access to League of Legends esports data including live matches, schedules, leagues, event details, and VODs through a standardized interface.
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    GPL 3.0
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    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.
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    MIT
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    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.
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    MIT
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    MCP server for reading Fonbet sports events and odds, enabling search for events, retrieval of odds, and value-bet checking via natural language.
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    A server that integrates Sleeper fantasy sports data with Goose AI through the Machine Context Protocol (MCP), providing structured access to fantasy league information.
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    Enables querying RGL.gg competitive TF2 data through natural language, resolving player, team, season, division, and match information via a series of API calls.
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    MCP server for natural language analysis of baseball league data, enabling team statistics, standings, lineup suggestions, and scouting reports via Claude Desktop.
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    Enables natural language querying of football/soccer data via the API-Football service, providing access to leagues, teams, players, fixtures, standings, and statistics.
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    Enables management of sports video metadata with PostgreSQL backend, supporting CRUD operations, advanced search, and tracking of game information including teams, scores, player statistics, and match details.
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    An MCP server that enables natural language querying of over 10 million ball-by-ball cricket deliveries stored in a local DuckDB database. It provides 26 tools for analyzing player matchups, situational stats, and historical records across all major cricket formats and tournaments.
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    Finds marked hiking routes from OpenStreetMap filtered by locally-computed elevation gain, distance, loop shape, and car/chairlift access, providing consistent and tunable metrics instead of third-party scraped data.
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    MIT
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    A local MCP server that gives Claude (or any MCP-compatible AI client) access to Formula 1 race data. Load any session from 2018 onwards, ask questions in natural language, and get answers backed by real telemetry, timing, and strategy data.
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    MIT