MCP Tic-Tac-Toe

The MCP Tic‑Tac‑Toe server turns a classic board game into a fully‑featured AI‑friendly toolset. By exposing a collection of well‑defined MCP tools, it lets assistants such as Claude create, manage, and analyze multiple game sessions without any custom UI logic. This is especially valuable for developers building interactive demos, teaching AI reasoning, or prototyping game‑theoretic algorithms in a conversational context.

At its core, the server offers eight intuitive tools that cover every phase of gameplay: from session creation () and state inspection (, ) to move execution () and strategic insight (). Each tool returns a JSON payload that the assistant can parse, display, or feed into subsequent prompts. The ability to reset or list active games makes it easy to run parallel sessions, enabling comparative studies of different AI strategies or human‑AI collaborations.

Developers benefit from the server’s transport flexibility. It can run over standard input/output for local clients like Claude Code, or via HTTP/SSE on a network port for remote integration. This means the same MCP contract can be leveraged in IDEs, web dashboards, or even embedded systems. The server’s modular design also allows extensions: additional analysis tools (e.g., minimax evaluation) could be added with minimal changes to the existing contract.

Real‑world use cases abound. In educational settings, instructors can demonstrate how an AI evaluates board positions and chooses optimal moves while students observe the underlying data flow. In research, the server can serve as a testbed for reinforcement learning agents that learn to play tic‑tac‑toe by interacting through the MCP interface. For product teams, it can be embedded in chatbots to provide quick, rule‑based games that keep users engaged during support interactions.

Overall, the MCP Tic‑Tac‑Toe server exemplifies how a simple game can become a powerful illustration of AI tool integration. It showcases the elegance of MCP’s standardized contracts, provides developers with a ready‑made playground for AI reasoning, and opens the door to richer, data‑driven conversational experiences.