MCP Multi-Server Demo with SSE Transport

What is MCP Multi-Server Demo with SSE Transport? This project demonstrates the use of the Model Context Protocol (MCP) with multiple servers utilizing different transport methods, specifically stdio and Server-Sent Events (SSE). It integrates with LangChain to create an agent capable of utilizing tools from both a math server and a weather server. How to use MCP Multi-Server Demo? To use this project, clone the repository, install the required dependencies, set up your OpenAI API key, and run the main application. The application will start the servers and allow you to perform queries. Key features of MCP Multi-Server Demo? Demonstrates the use of MCP with multiple servers. Provides a math server for basic arithmetic operations. Offers a weather server that simulates weather information. Integrates with LangChain to create an intelligent agent. Use cases of MCP Multi-Server Demo? Performing arithmetic calculations through the math server. Retrieving simulated weather information from the weather server. Extending the project to include more servers or functionalities. FAQ from MCP Multi-Server Demo? What programming language is used? The project is developed in Python. Do I need an OpenAI API key? Yes, you need to set up your OpenAI API key to use the agent functionality. Can I extend the project? Yes, you can add more tools or servers and modify the agent for more complex queries.

As an MCP (Model Context Protocol) server, MCP Multi-Server Demo with SSE Transport enables AI agents to communicate effectively through standardized interfaces. The Model Context Protocol simplifies integration between different AI models and agent systems.

To use this project, clone the repository, install the required dependencies, set up your OpenAI API key, and run the main application. The application will start the servers and allow you to perform queries. Key features of MCP Multi-Server Demo? Demonstrates the use of MCP with multiple servers. Provides a math server for basic arithmetic operations. Offers a weather server that simulates weather information. Integrates with LangChain to create an intelligent agent. Use cases of MCP Multi-Server Demo? Performing arithmetic calculations through the math server. Retrieving simulated weather information from the weather server. Extending the project to include more servers or functionalities. FAQ from MCP Multi-Server Demo? What programming language is used? The project is developed in Python. Do I need an OpenAI API key? Yes, you need to set up your OpenAI API key to use the agent functionality. Can I extend the project? Yes, you can add more tools or servers and modify the agent for more complex queries.

Learn how to integrate this MCP server with your AI agents and leverage the Model Context Protocol for enhanced capabilities.