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Multi-Agent Thinking MCP Server

@Hajime-Y

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

Apache-2.0 license

トランスポート

stdio

作者

Hajime-Y

Multi-Agent Thinking MCP Server について

MCP server for multi-agent thinking using smolagents

Multi-Agent Thinking 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": {
    "multiagents-thinking": {
      "command": "uv",
      "args": [
        "venv"
      ]
    }
  }
}

Multi-Agent Thinking 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 Multi-Agent Thinking MCP Server?

Multi-Agent Thinking MCP Server is a server that generates multiple specialist agents to tackle complex tasks from different perspectives and approaches in parallel. It is built on HuggingFace’s smolagents library and FastMCP, and is designed for users who need deep, multi‑angle analysis or solution generation.

How to use Multi-Agent Thinking MCP Server?

Clone the repository, create a virtual environment with uv, install dependencies with uv sync, then set OPENAI_API_KEY and HF_TOKEN in a .env file. Start the server with uv run python -m src.multiagents. MCP clients such as Cursor IDE can invoke the tool via multiagent.multiagent_thinking. For Claude Desktop, add a configuration entry in the MCP servers settings.

Key features of Multi-Agent Thinking MCP Server

  • Automatically generates multiple perspectives from a single task description.
  • Runs specialist agents in parallel, each focusing on a distinct approach.
  • Supports diverse problem‑solving strategies: perspective sharing, task sharing, stage sharing, parallel solving, branch search, and decomposition‑reconstruction.
  • Integrates reports from all specialists into a final conclusion or solution.

Use cases of Multi-Agent Thinking MCP Server

  • Analyze a design problem from several disciplinary viewpoints simultaneously.
  • Generate competing solution approaches for a complex task.
  • Decompose a large problem into sub‑tasks handled by separate specialist agents.

よくある質問

1

What are the runtime requirements?

Python 3.11 or later, the `uv` package manager, and API keys for OpenAI and HuggingFace.

2

What API keys are needed?

You must provide `OPENAI_API_KEY` and `HF_TOKEN` in a `.env` file at the project root.

3

How do I configure Multi-Agent Thinking MCP Server for Claude Desktop?

Add a JSON entry to your Claude Desktop configuration (e.g., `~/.config/Claude/claude_desktop_config.json`) with the absolute path to `uv` and to the project directory, using `uv run python -m src.multiagents` as the command.

4

How do I start the server?

Run `uv run python -m src.multiagents` from the project root after installing dependencies and setting environment variables.

5

What tool does the server expose?

It exposes the `multiagent.multiagent_thinking` tool for MCP clients to call.

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