Chess.com MCP Server

The Chess.com MCP Server turns the rich public data of one of the world’s largest chess platforms into a structured, AI‑friendly interface. By exposing player profiles, game archives, club information, and real‑time status through the Model Context Protocol, developers can embed up-to-date chess analytics directly into conversational agents without managing authentication or API keys. This removes a significant barrier for AI assistants that need to answer questions about player performance, historical game trends, or club activity.

At its core, the server offers a collection of well‑defined tools that map directly to Chess.com’s REST endpoints. Clients can retrieve a player’s profile, view cumulative statistics, or check whether a user is currently online. For deeper analysis, the server provides access to monthly game archives and allows downloading PGN files for bulk study. Club‑centric tools expose club profiles and member lists, enabling assistants to discuss community dynamics or recommend clubs to new players. All these capabilities are delivered over a simple, stateless protocol that requires no authentication—making it immediately usable in sandboxed or public environments.

Developers benefit from the server’s modularity and Docker support. The tool list is configurable, so a deployment can expose only the functions that fit a given use case. Whether building an educational chatbot that walks users through their own game history, a competitive analysis tool for tournament organizers, or a social platform that recommends clubs based on player activity, the Chess.com MCP Server plugs cleanly into existing AI workflows. Claude Desktop users, for example, can add the server via a single configuration entry and start querying chess data with natural language prompts.

Unique advantages include zero‑auth convenience, comprehensive coverage of Chess.com’s public data, and the ability to download full PGN archives for offline processing. Because the server runs in a container or via UV, it can be deployed locally or on cloud infrastructure with minimal overhead. In practice, this means a developer could build an AI tutor that not only explains chess concepts but also pulls the student’s recent games to provide personalized feedback, all without writing custom API wrappers. The Chess.com MCP Server thus democratizes access to high‑quality chess data, enabling richer, more interactive AI experiences.