MCP Sse

What is mcp-sse

mcp-sse is an innovative server solution developed by sidharthrajaram that implements a working pattern for Server-Sent Events (SSE)-based Model Context Protocol (MCP) servers. It is designed to facilitate seamless interactions between standalone MCP clients and tools hosted on these servers. The core purpose of mcp-sse is to allow AI systems to securely connect with various data sources and tools, enabling AI assistants to access real-time information and perform context-based queries.

By leveraging the power of SSE, mcp-sse allows clients to connect, use, and disconnect from server processes flexibly, making it ideal for cloud-native applications. This decoupled architecture means that the server and clients can run independently, even on separate nodes, offering a robust alternative to traditional STDIO-based communication patterns.

How to Use mcp-sse

Using mcp-sse involves running both a server and a client component. Here's a step-by-step guide to get started:

1. Set Up Environment: Ensure you have the ANTHROPIC_API_KEY set in your environment variables or within a .env file. This API key is essential for authenticating and connecting to the necessary data sources.

2. Start the Server: Use the following command to run the SSE-based MCP server:

   uv run weather.py
   

   By default, the server operates on 0.0.0.0:8080, but you can configure this with command-line arguments to suit your needs.

3. Run the Client: Connect to the server with the client by executing:

   uv run client.py http://0.0.0.0:8080/sse
   

   The client will initialize, list available tools, and establish a connection to the server.

4. Interact with the Server: Once connected, you can start typing queries such as "What's the weather like in Spokane?" The client will utilize functions like get_forecast to retrieve and display the weather data based on the query parameters.

5. Exiting: Type 'quit' to disconnect from the server and exit the client.

Key Features of mcp-sse

• Decoupled Architecture: mcp-sse supports a decoupled client-server model, allowing flexibility in deployment and scalability. This architecture is especially beneficial for cloud-native applications.

• Seamless Integration: By utilizing the Model Context Protocol, mcp-sse allows AI systems like Claude to securely access external data sources, tools, and prompts, enhancing the AI's ability to provide accurate and contextually relevant information.

• Real-time Data Access: The server can expose various data sources, enabling real-time access to files, documents, databases, and APIs. This ensures that AI assistants can process and respond to queries with up-to-date information.

• Tool Utilization: Clients can list and use tools available on the server, such as get_alerts and get_forecast, which are based on National Weather Service APIs. This functionality allows for executing specific functions tailored to the user's queries.

• Flexible Configuration: Both the server and client can be configured with command-line arguments, allowing users to specify custom host and port settings, enhancing the adaptability of the system to different environments.

mcp-sse is a powerful tool for developers and AI enthusiasts looking to harness the potential of SSE-based communications in AI applications, providing a secure, flexible, and efficient platform for data-driven interactions.