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"Chess game information and resources" matching MCP servers:

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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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    2
    MIT
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    An MCP server that exposes Stockfish chess analysis to LLM chat clients, enabling move analysis, game review, and explanation of engine choices.
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    Provides access to Chess.com player data, game records, and public information through standardized MCP interfaces, allowing AI assistants to search and analyze chess information.
    Last updated
    10
    79
    MIT
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    Provides tools to interact with the Chess.com Public API for fetching real-time player profiles and detailed game statistics. It enables LLMs to access information like player ratings, win/loss records, and current online status.
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    MCP server for Myers Park High School athletics, providing public access to schedules, teams, rosters, coaches, news, and game broadcast links.
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    10
    MIT
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    An MCP server that connects Claude Desktop to Hudl, enabling live access to team stats, player stats, and game results through natural language queries.
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    MCP server that exposes the Lichess public API through tools for querying player profiles, games, analysis, openings, puzzles, and tournaments, allowing natural-language chess questions without an API key.
    Last updated
    8
    MIT
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    Provides game rules, roster constraints, FAQ, and official links for the 27-0 NRL fantasy draft game, enabling AI clients to retrieve this knowledge.
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    2
    MIT
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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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    19
    MIT
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    Connects Claude to Lichess for playing chess games, analyzing positions with Stockfish cloud evaluation, and solving puzzles. Supports real-time gameplay including moves, challenges, draw offers, and accessing user profiles and game history.
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    28
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    MIT
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    Exposes the canonical 17-0 knowledge surface including game rules, roster constraints, and entry points for the NFL roster strategy game to MCP-compatible AI clients.
    Last updated
    2
    MIT