LangGraph Agent with MCP
by galaxyxyz5
This project integrates Model Context Protocol (MCP) with a LangGraph Agent, enabling dynamic access to external tools and data sources. It allows AI systems to automatically discover tools and connect to multiple servers, increasing their flexibility and efficiency.
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What is LangGraph Agent with MCP?
This project is a LangGraph agent that leverages the Model Context Protocol (MCP) to dynamically connect to external tools, data sources, and APIs. It allows the agent to automatically discover and utilize various tools hosted on MCP servers, such as web search, YouTube transcript summarization, and more.
How to use LangGraph Agent with MCP?
First, clone the repository and install the dependencies using pip install -r requirements.txt. Create a .env file and add your API keys for Tavily and OpenAI. Start the MCP server by running servers/server.py in one terminal. Then, in a new terminal, run agent.py to connect the agent to the server and execute queries.
Key features of LangGraph Agent with MCP
Dynamic tool discovery via MCP
Multi-server support
Integration with LangGraph
Modular architecture for adding new tools
Automatic connection to external data sources
Use cases of LangGraph Agent with MCP
Automated research and information gathering
Intelligent task automation
Dynamic access to real-time data
Building AI systems that can adapt to new tools
Orchestration of multiple tools for complex tasks
FAQ from LangGraph Agent with MCP
What is MCP?
What is MCP?
MCP (Model Context Protocol) is an open standard that provides a structured way for AI applications to interact with external data, tools, and APIs.
Why use MCP with LangGraph?
Why use MCP with LangGraph?
MCP allows LangGraph agents to dynamically access a wide range of tools without requiring custom integrations for each tool.
How do I add a new tool?
How do I add a new tool?
You can add a new tool by creating a new server file in the servers/ directory and implementing the MCP interface.
What API keys do I need?
What API keys do I need?
You need API keys for Tavily and OpenAI, which should be added to the .env file.
How do I run the agent?
How do I run the agent?
First, start the MCP server by running servers/server.py. Then, in a new terminal, run agent.py.