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Minesweeper MCP Server

MCP Server

Play Minesweeper through Model Context Protocol

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Updated 22 days ago

About

A Model Context Protocol server that lets MCP client agents play Minesweeper by interacting with a separate game server. It provides tools for starting games, making moves, and flagging mines via MCP commands.

Capabilities

Resources
Access data sources
Tools
Execute functions
Prompts
Pre-built templates
Sampling
AI model interactions

Minesweeper MCP Server in action

The Minesweeper MCP Server is a lightweight bridge that lets AI agents—such as Claude or other Model Context Protocol (MCP) clients—interact with a classic Minesweeper game. Rather than building a custom game‑playing routine from scratch, developers can expose the full set of Minesweeper actions (e.g., opening a cell, placing or removing a flag) through the MCP interface. This enables AI assistants to play the game autonomously, solve puzzles, or even teach users how to navigate a board by providing step‑by‑step guidance.

At its core, the server translates MCP tool calls into HTTP requests that target an existing Minesweeper game backend. Each call corresponds to a single move: opening a tile, toggling a flag, or querying the current board state. The server then returns structured JSON that the AI can consume to update its internal context, decide on the next action, or report results. Because the protocol is stateless and purely request‑response, it integrates seamlessly into any AI workflow that already relies on MCP tools. Developers can simply add the server as a new tool in their client configuration, and the assistant will automatically discover and use it.

Key capabilities include:

  • Full board manipulation – Open or flag any coordinate, with 0‑based indexing that matches the game’s API.
  • State inspection – Retrieve the current board layout, mine counts, and whether the game is won or lost.
  • Game lifecycle control – Start a new game, reset an existing one, and monitor progress.
  • Error handling – The server reports invalid moves or out‑of‑bounds coordinates, allowing the AI to adjust its strategy.

Real‑world scenarios where this MCP server shines are plentiful. A developer could build a “playthrough assistant” that automatically solves puzzles, logs the solution path for analytics, or generates tutorials. Game‑testing pipelines could incorporate AI agents that play randomly to surface edge cases. Educational tools might let students interact with an AI tutor that demonstrates Minesweeper tactics in real time.

Because the server is built on top of a proven game backend, it offers reliability and speed. Its integration requires only minimal configuration: add the tool to your MCP client, start the game server locally, and let the AI orchestrate gameplay. This makes it an attractive option for teams looking to prototype AI‑driven game interactions or embed intelligent gameplay into larger applications without reinventing the underlying mechanics.