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

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 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.

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

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.

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 an LLM client to download a player's chess.com games, check every move with Stockfish, and answer questions about why games were lost, which mistakes repeat, and what to practise. Returns code-computed reports on loss causes, weekly focus, trends, opening and clock weaknesses, motif tags, and peer comparison with noise margins.

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

Enables playing chess against an AI agent or pitting two agents against each other on a live web board, with a built-in rules engine that enforces legal moves, turn order and complete FIDE rules so agents cannot hallucinate or cheat. Includes human-vs-agent play, agent-vs-agent spectator mode with optional Stockfish evaluation, and PGN game review.

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.

Enables humans, built-in engines, Claude API models, and AI agents to play chess against each other through MCP or CLI, with text and image board views, move validation, turn waiting, and live spectating.

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.

Enables any AI assistant to fetch Lichess and Chess.com games, analyze them with Stockfish, and explain mistakes, critical moments, opening weaknesses, and recurring patterns in plain language.

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 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.

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 local chess move validation and game state management for standard and variant rules via MCP, without engine recommendations.

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.

Enables chess position analysis, legal move investigation, move comparison, and PGN game reconstruction through MCP tools.

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.

Play interactive chess games through conversation with move validation, Stockfish engine analysis, tactical puzzles, and a visual chess board widget in ChatGPT.