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    Enables AI agents to discover live and recent football matches, scores, and fan clips on Vublox. Supports searching by team, league, or keyword and retrieving match summaries.
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    MIT
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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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    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.
    4
    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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    A Model Context Protocol server that provides comprehensive Formula One racing data, enabling access to event schedules, driver information, telemetry data, race results, and performance analytics through natural language queries.
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    Provides Chess.com player data integration, enabling AI assistants to fetch real-time chess player profiles and comprehensive statistics including ratings, game counts, and performance metrics from Chess.com's public API.
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    MIT
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    Provides seamless access to iRacing's racing simulation data, enabling AI assistants to retrieve driver profiles, career statistics, and team information. It features automatic authentication and tools for real-time driver lookups and season performance analysis.
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    Enables Formula 1 data analysis through natural language, providing tools like track dominance, lap time analysis, and team performance comparisons.
    Apache 2.0
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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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    Enables analysis of GeoGuessr game statistics, performance tracking, and strategy recommendations with automatic API monitoring and multi-user support. Features dynamic schema adaptation to handle GeoGuessr API changes automatically.
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    An MCP server that provides access to over 12 years of NFL play-by-play data through a local DuckDB database. It enables users to query player performance, team statistics, and situational efficiency metrics like EPA and WPA using natural language.
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    MIT
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    Governed data pipeline for NBA ticketing and attendance data, exposing typed tools for AI agents to query game performance and seat-tier sales without direct database access.
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    Provides AI agents with direct access to KingsPlaybook's sports data including confirmed lineups, player projections, game lines, and pick history via native MCP tools.
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    MCP server that connects Claude or any MCP-capable LLM to your Garmin golf data, enabling natural-language queries on rounds, shots, strokes gained, club distances, course intel, and health-performance correlations from a private local DuckDB cache.
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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