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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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    Self-hosted football social-media agent that drafts posts, generates assets, and requires Telegram approval before publishing, with stateful SQLite storage and async image jobs.
    MIT
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    Provides professional cycling data from ProCyclingStats, enabling race discovery, stage results, rider profiles, startlists, and free-text search through MCP tools.
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    The Unlicense
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    Retrieves and displays the latest horse racing news stories from Thoroughbred Daily News RSS feed, including titles, content, and links.
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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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    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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    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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    MCP server that gives Claude programmatic access to a local En Croissant chess opening trainer, enabling conversational opening prep by reading its SQLite database, PGN files, and Lichess API. It supports repertoire review, due cards, and opponent statistics directly from chat.
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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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    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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    Live sports betting player props MCP server covering NBA, MLB, NFL, NHL, NCAA, and soccer. Unified from real sportsbooks into one REST API and a real MCP server (Streamable HTTP). Free tier, no card required.
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    MIT
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    Real-time prediction market consensus data for AI agents. Aggregates probabilities from 27,000+ markets across politics, sports, and economics with 14-second updates. Tools: get_markets, get_consensus, get_movers, get_divergences, search_markets.
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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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    Connects AI assistants to SharpEdge AI to discover +EV sports betting opportunities and arbitrage edges across major sportsbooks. It provides real-time scanner statistics, sample betting edges, and educational content on advanced betting concepts like the Kelly Criterion.
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    Provides professional cycling data from FirstCycling, allowing users to retrieve comprehensive information about cyclists, race results, historical cycling data, and team information through natural language queries.
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    Provides AI-powered sports analytics for Daily Fantasy Sports (DFS) with real-time player projections, lineup optimization, live odds aggregation from multiple sportsbooks, and SHAP-based explainability to understand recommendation reasoning.
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    MIT