LANGGRAPH MCP AGENTS

@serkanyasr

代码仓库

基本信息

分类

推理

许可证

MIT license

传输方式

stdio

作者

serkanyasr

关于 LANGGRAPH MCP AGENTS

Transforms MCP tools into collaborative agents using the LangGraph framework.

#mcp #agents #langgraph #mcp-server

LANGGRAPH MCP AGENTS 配置

暂无标准配置

该服务器的 README 中没有可解析的 MCP 配置块，请前往代码仓库查看安装说明。

代码仓库

LANGGRAPH MCP AGENTS 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is LANGGRAPH-MCP-AGENTS?

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.

How to use LANGGRAPH-MCP-AGENTS?

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.

Key features of LANGGRAPH-MCP-AGENTS

Transforms MCP tools into LangGraph‑powered autonomous agents.
Manages multiple MCP server connections and tool initialization.
Provides a command‑line chatbot interface using the OpenAI language model.
Supports tool execution and resource cleanup via MCPServer class.
Configurable via mcp_config.json for filesystem, SQLite, and memory servers.
Licensed under the MIT License – free to use, modify, and distribute.

Use cases of LANGGRAPH-MCP-AGENTS

Converting existing MCP tools (e.g., code execution, planning) into collaborative agents.
Building a multi‑agent chatbot that delegates tasks to different MCP servers.
Experimenting with agent orchestration on top of the MCP protocol using LangGraph.
Prototyping autonomous workflows that combine filesystem, database, and memory tools.

常见问题

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`.

How do I install LANGGRAPH-MCP-AGENTS?

Clone the repository, navigate to the project directory, and run `pip install -r requirements.txt`. No additional package manager is needed.

Is LANGGRAPH-MCP-AGENTS production-ready?

No. The project is explicitly marked as experimental and intended for exploration and prototyping.

What servers are supported by default?

The `mcp_config.json` provides example configurations for filesystem, SQLite, and memory MCP servers. The `MCPClient` class can load arbitrary server configurations.

How are MCP servers managed?

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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