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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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    An MCP server that integrates with the Playtomic API to find nearby padel courts, check availability, compare prices, and set alerts for preferred slots.
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    A server for querying surf spot data and searching spots, with tools to list regions, spots, get spot info, find spots by criteria, and get mock forecasts.
    MIT
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    An MCP server that answers football questions with interactive widgets, centered on the 2026 FIFA World Cup using SofaScore API data.
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    Provides intelligent access to OPTA football API documentation with automatic authentication, allowing users to query specific endpoint documentation and get answers about soccer match data, events, fixtures, and statistics through natural language.
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    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.
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    Provides access to real-time data from the French Basketball Federation (FFBB), including live scores, standings, and competition details. It allows users to search for clubs, matches, and venues using natural language without requiring an API key.
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    Apache 2.0
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    Tells you when your favourite football teams play and where to watch in Denmark, using data from TheSportsDB.com and built-in Danish broadcast hints.
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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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    Read-only MCP server for Counter-Strike schedules, results, teams, players, and events from HLTV.org, offering tools to search entities, list matches, and get match details.
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    MIT
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    Enables AI agents to query live sports betting data including odds, edges, arbitrage opportunities, player/team stats, and reference data using the SportWizzard API.
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    MIT
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    Enables users to query MLB Statcast, FanGraphs, and Baseball Reference data using natural language through an AI assistant. It provides comprehensive tools for analyzing player performance, pitch-level data, season leaderboards, and team standings.
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    MIT
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    Provides access to KenPom basketball analytics through MCP tools. Enables querying ratings, efficiency, player stats, and more using natural language.
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    MIT
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    Enables AI agents to search and retrieve detailed information about US golf courses, including course details, tees, climate, and nearby points of interest.
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    MIT
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    Provides AI-powered sports betting intelligence including live odds, injury reports, and documented picks for NBA, NHL, and NCAAB. It enables AI agents to analyze line movements, win rates, and betting edges using real-time data from sportsbettingaianalyzer.com.
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    MIT
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    Provides comprehensive running performance calculations including VDOT, training paces, race time predictions, velocity markers, and heart rate zones using Jack Daniels, Greg McMillan, and Riegel methodologies.
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    MIT
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    Enables AI assistants to analyze Fantasy Premier League data, providing tools for player search, fixture analysis, manager comparisons, and strategy prompts for transfer planning and lineup selection.
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    MIT
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    Provides soccer match predictions and league statistics using xG data and Poisson distribution models. It enables users to forecast outcomes, analyze team performance, and view league tables across major European football leagues.
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    GPL 2.0
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    MCP server for motorsport event documents, enabling AI agents to search, read, compare amendments, and parse schedules via typed tools.
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