Enables Large Language Models to play chess agentically with real-time HTML board visualization and a hybrid AI engine featuring ten difficulty levels. It supports interactive games between users and agents, including a web dashboard to monitor active matches.
A powerful chess engine and game server built with the Model Context Protocol (MCP). Play chess against AI, analyze positions, and integrate chess functionality into your AI applications.
MCP chess runtime that lets LLMs play, analyze, and adapt strength by exposing Stockfish, human move likelihood (Maia3), and Lichess statistics, with the LLM handling strategy and the server handling computation.
A server that enables users to play chess against any LLM, with features for visualizing the board, making moves in standard notation, and analyzing positions from PGN files.
A Model Context Protocol server that enables LLM agents and humans to play chess games together with comprehensive game management capabilities including move validation, draw detection, and game state tracking.
