What is the Model Context Protocol (MCP)?
MCP is an open standard that lets AI models interact with external tools and data sources, solving context limitations, tool integration, interoperability, and extensibility challenges.
@panz2018
Basic information
A working example to create a starlette server with SSE-based MCP support
No standard config provided
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It is a Server-Sent Events (SSE) implementation using the Starlette framework with Model Context Protocol (MCP) integration. The project demonstrates how to add MCP SSE endpoints to a Starlette web application while keeping standard web routes separate.
You can run the server without cloning via uvx --from git+https://github.com/panz2018/starlette_mcp_sse.git start, or install fully with uv venv, activate it, install dependencies with uv pip install -r pyproject.toml, then start with python src/server.py or uv run start. After startup, the SSE endpoint is at /sse and message endpoint at /messages/. Debug using MCP Inspector with the mcp dev ./src/weather.py command and connect at http://localhost:8000/sse.
MCP is an open standard that lets AI models interact with external tools and data sources, solving context limitations, tool integration, interoperability, and extensibility challenges.
You need the UV Package Manager installed. The recommended install command is: `powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"`.
Standard web routes: `/`, `/about`, `/status`, `/docs`. MCP SSE endpoints: `/sse` (SSE stream) and `/messages/` (message posting). The main server runs on `http://localhost:8000`.
Use the MCP Inspector by running `mcp dev ./src/weather.py`, open `http://localhost:5173`, set Transport Type to SSE, enter URL `http://localhost:8000/sse`, and click Connect. Then list and test tools like `get_alerts` and `get_forcast`.
Add the following JSON to your Continue settings under `experimental.modelContextProtocolServers`: `{"transport":{"name":"weather","type":"sse","url":"http://localhost:8000/sse"}}`.
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