"Chess game information and resources" matching MCP servers:

Enables MCP agents to play chess locally, supporting join, state, legal moves, and move execution with per-session color ownership.

Enables two autonomous LLM agents to play a full game of chess against each other over MCP, with turn order, legality, clocks, and move history enforced server-side outside both models so neither player can cheat or desync the position, while a live WebSocket GUI lets spectators watch.

Enables users to play interactive chess against the model inside ChatGPT, with the user taking white and the model black on a rendered board. Provides tools to start and end games, validate and apply both user and model moves, and retrieve the authoritative FEN, PGN, legal moves, and game history.

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.

Enables AI agents to play and analyze chess, validate moves, and view a live synchronized visual board in the browser through MCP tools.

Provides an interactive chess game experience through MCP tools with a web-based chessboard interface. Enables users to play chess games, make moves using standard algebraic notation, and manage persistent game state across sessions.

Multi-dimensional chess analysis MCP server using Zero Divisor Transmission Protocol, evaluating positions across tactical, positional, and strategic layers with gateway convergence detection.

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.

MCP server for playing chess matches between AI agents across computers, enabling match creation, move submission, and turn waiting.

Lets Claude join a real match of the shooting game as the second player and play it through a live browser, reading the arena and sending actual keyboard inputs to move and shoot.

A hybrid AI chess coach MCP server that uses Stockfish for grounded evaluation and LLM for natural-language coaching, enabling game analysis, weakness diagnosis, and personalized drills from your own games.

Enables AI assistants to play chess against users, manage games, make moves, and visualize boards with Stockfish AI opponent.

Manages the state of a chess game for LLMs/agents without suggesting moves, providing tools to create/reset game, add moves, get status, and check legality.

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.

Web scraper and token compressor that converts HTML to clean markdown with 70-80% fewer tokens. Single-page compression and multi-page BFS crawling with auto-fallback fetch modes.

Enables AI assistants to play, analyze, and track chess games with full rule validation and support for standard algebraic notation. It provides tools for position evaluation and game state persistence during user sessions.

A Model Context Protocol server that enables Claude to execute Python code using boto3 to query and manage AWS resources directly from conversations.

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.

MCP server that demonstrates the Resources feature by exposing static and dynamic resources, including contact data and personalized greetings, through MCP.

LLM routing proxy that cuts API costs 60-90% by auto-selecting the cheapest capable model across OpenAI, Anthropic, and Google. Provides stats, config, and model comparison tools via MCP.