What are the runtime requirements?
Python and pip are required. All dependencies are listed in `requirements.txt` and include `mcp`, `langgraph`, `langchain`, `python-dotenv`, `langchain-mcp-adapters`, and `rich`.
@serkanyasr
基本情報
Transforms MCP tools into collaborative agents using the LangGraph framework.
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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。
LangGraph MCP Agents is an experimental project that transforms tools defined under the Modular Communication Protocol (MCP) into autonomous agents using the LangGraph framework. It enables effective task sharing and collaboration between these agentified MCP tools, such as planning, coding, and execution tasks.
Clone the repository, install dependencies with pip install -r requirements.txt, then run python app_cli.py to start the CLI chatbot. The project uses a mcp_config.json to configure MCP servers (filesystem, SQLite, memory) and an mcp_client.py module to manage server connections and tool execution.
mcp_config.json for filesystem, SQLite, and memory servers.Python and pip are required. All dependencies are listed in `requirements.txt` and include `mcp`, `langgraph`, `langchain`, `python-dotenv`, `langchain-mcp-adapters`, and `rich`.
Clone the repository, navigate to the project directory, and run `pip install -r requirements.txt`. No additional package manager is needed.
No. The project is explicitly marked as experimental and intended for exploration and prototyping.
The `mcp_config.json` provides example configurations for filesystem, SQLite, and memory MCP servers. The `MCPClient` class can load arbitrary server configurations.
The `mcp_client.py` module contains `MCPClient` and `MCPServer` classes. `MCPClient` manages connections to multiple servers, starts them, initializes tools, and handles cleanup.
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