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MCTS MCP Server

@angrysky56

リポジトリ

基本情報

カテゴリ

AI とエージェント

ライセンス

MIT

トランスポート

stdio

作者

angrysky56

MCTS MCP Server について

Bayesian MCTS Model Context Protocol Server allowing Claude to control Ollama local models for Advanced MCTS and analysis.

#ai#mcts#bayesian#claude#mcp-server

MCTS MCP Server の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "mcts-mcp-server": {
      "command": "python",
      "args": [
        "setup.py"
      ]
    }
  }
}

MCTS MCP Server のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is MCTS MCP Server?

The MCTS MCP Server is a Model Context Protocol server that exposes an Advanced Bayesian Monte Carlo Tree Search (MCTS) engine for AI-assisted analysis and reasoning. It enables AI assistants like Claude to systematically explore different angles and interpretations of a topic, question, or text input using a probabilistic MCTS algorithm.

How to use MCTS MCP Server?

Install via the automatic setup script (python setup.py) or manually using UV. Configure API keys in a .env file and add the server’s configuration to Claude Desktop’s config file. Once set up, the AI assistant can call tools like initialize_mcts, run_mcts, generate_synthesis, and set_active_llm to perform deep analysis.

Key features of MCTS MCP Server

  • Bayesian MCTS: balances exploration vs. exploitation probabilistically
  • Multi-iteration analysis with multiple simulations per iteration
  • State persistence across chat turns
  • Approach taxonomy classifying thoughts into philosophical families
  • Thompson sampling or UCT for node selection
  • Surprise detection for novel analysis directions

Use cases of MCTS MCP Server

  • Deep analysis of complex topics or questions
  • Exploring multiple interpretations of a text input
  • Iterative reasoning with state persistence across chat turns
  • Comparing analytical pathways generated by different MCTS configurations
  • Using local or cloud LLMs to drive MCTS analysis

よくある質問

1

What runtime and dependencies are required?

Python 3.10+ and the UV package manager. Dependencies are installed automatically by the setup script.

2

How do I obtain and configure API keys?

Edit the `.env` file created during setup with your API keys for OpenAI, Anthropic, and/or Google Gemini. For Ollama, no API key is needed.

3

Does the MCTS server call the LLM directly?

No. The server uses a local inference approach; it does not call the LLM directly. It provides tools that the AI assistant (e.g., Claude) calls to perform MCTS analysis.

4

What should I do if Claude Desktop does not detect the server?

Verify the config file location and syntax, ensure paths are absolute and correct, restart Claude Desktop completely, and check Claude Desktop logs

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