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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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    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.
    10
    MIT
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    MCP server for Bosch eBike Flow (Smart System / BES3). Read-only access to battery health and charge-cycle trends, components and firmware, live state-of-charge, and per-ride activity data (distance, elevation, power, assist-mode, CO2), signing in with your own Bosch account via PKCE.
    12
    GPL 3.0
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    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.
    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 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.
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    Enables Fantasy Premier League squad management with custom tools for player search, fixture outlook, tier classification, hit math, and chip timing, all using public FPL data without requiring login credentials.
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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 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.
    4
    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
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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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    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.
    9
    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.
    3
    GPL 2.0