MCP architecture demo with single-server & multi-server clients using LangGraph, AI-driven tool calls, and async communication.
Overview
What is LangGraph MCP Integration?
LangGraph MCP Integration is a project that demonstrates the Multi-Client Protocol (MCP) architecture, showcasing how to efficiently connect AI-driven applications with multiple external services through single-server and multi-server clients.
How to use LangGraph MCP Integration?
To use this project, clone the repository, sync dependencies, and run the provided server and client scripts to interact with the Math and Weather servers.
Key features of LangGraph MCP Integration?
- Demonstrates single-server and multi-server client architectures.
- Provides basic mathematical operations and real-time weather information.
- Supports multiple transport layers for communication (stdio, SSE).
- Integrates AI models for dynamic tool invocation and processing.
Use cases of LangGraph MCP Integration?
- Performing mathematical computations using the Math server.
- Retrieving real-time weather data using the Weather server.
- Building scalable AI applications that require interaction with multiple services.
FAQ from LangGraph MCP Integration?
- What is MCP architecture?
MCP architecture allows seamless communication between AI models and various tool servers, enabling efficient processing of requests.
- Can I run both servers simultaneously?
Yes! You can run both the Math and Weather servers at the same time to utilize their functionalities in a multi-server client.
- What programming language is used in this project?
The project is implemented in Python.