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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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    MCP server that provides F1 telemetry analysis, tyre degradation modeling, and pit strategy recommendations, delivering race engineer-style calls grounded in real data. It exposes tools for degradation fits, fuel correction, and strategy reasoning via LangGraph.
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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.
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    MIT
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    Provides tools and resources to interact with the Fantasy Premier League API, enabling player analysis, fixture insights, and team management through natural language.
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    MCP server that connects AI assistants to the Statos football analytics platform, enabling natural language queries for match predictions, betting picks, league information, and admin market-suppression controls.
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    MIT
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    An MCP server that lets an LLM query a DuckDB warehouse of EuroLeague and EuroCup basketball data in natural language, offering tools for player and team stats, shot charts, boxscores, and fantasy draft analysis without contacting upstream APIs.
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    MIT
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    Searchable football data provider documentation for AI coding agents. Enables agents to look up verified docs on event types, qualifier IDs, coordinate systems, and more across 15 providers.
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    MIT
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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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    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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    NFL fantasy football data over MCP. Compare any two players head to head, pull position rankings in PPR, half-PPR or standard, check positional scarcity and bye-week conflicts.
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    MIT
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    Enables AI assistants to read your SisRUN training plan with your own credentials and answer questions about prescribed workouts, like weekly coach plans, in a structured format.
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    MIT
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    Enables AI assistants to monitor a Sleeper fantasy football draft in real time by retrieving draft picks, available players, current turn, and roster needs through Sleeper's public keyless API.
    8