"A search for information about chess" matching MCP servers:

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

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

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

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.

Helps you analyze chess positions and get professional evaluations using Stockfish.

An MCP bridge that provides an interface to UCI-compatible chess engines like Stockfish for analyzing positions and retrieving best moves. It enables users to interact with chess engines through commands for position management, engine information, and move calculation.

Enables querying Chess.com player profiles, ratings, game histories, and leaderboard rankings through a natural language MCP interface.

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.

Enables playing chess games with legal move validation and AI opponent moves powered by the Stockfish engine. Supports multiple concurrent games and provides moves in UCI format.

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 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.

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.

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.

Enables AI assistants to retrieve Chess.com player profiles, statistics, and daily puzzles through the Model Context Protocol.

Enables AI assistants to explore player profiles, ratings, game archives, leaderboards, clubs, and puzzles via the Chess.com API.

Enables local Stockfish-powered chess game analysis, mistake classification, puzzle finding and generation, and study-resource recommendations through MCP tools.

Enables voice-controlled chess against Maia or Stockfish, validating moves via a Pebble ring and rendering the board on a TRMNL e-ink display.