SSE-based MCP Server and Client
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# SSE-based Server and Client for [MCP](https://modelcontextprotocol.io/introduction) [](https://smithery.ai/server/@sidharthrajaram/mcp-sse) This demonstrates a working pattern for SSE-based MCP servers and standalone MCP clients that use tools from them. Based on an original discussion [here](https://github.com/modelcontextprotocol/python-sdk/issues/145). ## Usage **Note**: Make sure to supply `ANTHROPIC_API_KEY` in `.env` or as an environment variable. ``` uv run weather.py uv run client.py http://0.0.0.0:8080/sse ``` ``` Initialized SSE client... Listing tools... Connected to server with tools: ['get_alerts', 'get_forecast'] MCP Client Started! Type your queries or 'quit' to exit. Query: whats the weather like in Spokane? I can help you check the weather forecast for Spokane, Washington. I'll use the get_forecast function, but I'll need to use Spokane's latitude and longitude coordinates. Spokane, WA is located at approximately 47.6587° N, 117.4260° W. [Calling tool get_forecast with args {'latitude': 47.6587, 'longitude': -117.426}] Based on the current forecast for Spokane: Right now it's sunny and cold with a temperature of 37°F and ... ``` ## Why? This means the MCP server can now be some running process that agents (clients) connect to, use, and disconnect from whenever and wherever they want. In other words, an SSE-based server and clients can be decoupled processes (potentially even, on decoupled nodes). This is different and better fits "cloud-native" use-cases compared to the STDIO-based pattern where the client itself spawns the server as a subprocess. ### Installing via Smithery To install SSE-based Server and Client for Claude Desktop automatically via [Smithery](https://smithery.ai/server/@sidharthrajaram/mcp-sse): ```bash npx -y @smithery/cli install @sidharthrajaram/mcp-sse --client claude ``` ### Server `weather.py` is a SSE-based MCP server that presents so…
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