What MCP servers are included?
Three sample servers: `math_mcp_server`, `weather_mcp_server`, and `which_llm_to_use_mcp_server`, each with one or two functions.
@TaQuangTu
基本情報
Sample MCP Server & Client setup, compatible with LangChain
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。
MCP with Langchain Sample Setup is a demonstration project that implements the Model Context Protocol (MCP) with Langchain. It includes three sample MCP servers (math, weather, and which_llm_to_use), each exposing one or two functions, and a Streamlit-based MCP client that bridges users with those servers. It is intended for developers exploring MCP and Langchain integration.
Start each of the three MCP servers in the mcp_servers folder on ports 8000, 8001, and 8002 (e.g., nohup python math_mcp_server.py > math.log 2>&1 &). Then export your OpenAI API key and launch the Streamlit client with streamlit run my_chat_bot_app.py. The web UI will be available on port 8501.
Three sample servers: `math_mcp_server`, `weather_mcp_server`, and `which_llm_to_use_mcp_server`, each with one or two functions.
They listen on ports 8000, 8001, and 8002 respectively.
Set the `OPENAI_API_KEY` environment variable and run `streamlit run my_chat_bot_app.py`. The client starts a web UI on port 8501.
Yes, an OpenAI API key is required and must be set as the `OPENAI_API_KEY` environment variable.
Python is needed to run the servers and client. The project uses Streamlit and the OpenAI library, though exact dependency details are not listed in the README.

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