Starlette MCP SSE

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A Server-Sent Events (SSE) implementation using Starlette framework with Model Context Protocol (MCP) integration.

What is MCP?

The Model Context Protocol (MCP) is an open standard that enables AI models to interact with external tools and data sources. MCP solves several key challenges in AI development:

- Context limitations: Allows models to access up-to-date information beyond their training data
- Tool integration: Provides a standardized way for models to use external tools and APIs
- Interoperability: Creates a common interface between different AI models and tools
- Extensibility: Makes it easy to add new capabilities to AI systems without retraining

This project demonstrates how to implement MCP using Server-Sent Events (SSE) in a Starlette web application.

Description

This project demonstrates how to implement Server-Sent Events (SSE) using the Starlette framework while integrating Model Context Protocol (MCP) functionality. The key feature is the seamless integration of MCP's SSE capabilities within a full-featured Starlette web application that includes custom routes.

Features

- Server-Sent Events (SSE) implementation with MCP
- Starlette framework integration with custom routes
- Unified web application with both MCP and standard web endpoints
- Customizable route structure
- Clean separation of concerns between MCP and web functionality

Architecture

This project showcases a modular architecture that:

1. Integrates MCP SSE endpoints (/sse and /messages/) into a Starlette application
2. Provides standard web routes (/, /about, /status, /docs)
3. Demonstrates how to maintain separation between MCP functionality and web routes

Installation & Usage Options

Prerequisites

Install UV Package Manager - A fast Python package installer written in Rust:

powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"

Option 1: Quick Run Without Installation

Run the application directly without cloning the repository using UV's execution tool:

uvx --from git+https://github.com/panz2018/starlette_mcp_sse.git start

Option 2: Full Installation

Create Virtual Environment

Create an isolated Python environment for the project:

uv venv

Activate Virtual Environment

Activate the virtual environment to use it:

.venv\Scripts\activate

Install Dependencies

Install all required packages:

uv pip install -r pyproject.toml

Start the Integrated Server

Launch the integrated Starlette server with MCP SSE functionality:

python src/server.py

or

uv run start

Available Endpoints

After starting the server (using either Option 1 or Option 2), the following endpoints will be available:

- Main server: http://localhost:8000
- Standard web routes:
- Home page: http://localhost:8000/
- About page: http://localhost:8000/about
- Status API: http://localhost:8000/status
- Documentation: http://localhost:8000/docs
- MCP SSE endpoints:
- SSE endpoint: http://localhost:8000/sse
- Message posting: http://localhost:8000/messages/

Debug with MCP Inspector

For testing and debugging MCP functionality, use the MCP Inspector:

mcp dev ./src/weather.py

Connect to MCP Inspector

1. Open MCP Inspector at http://localhost:5173
2. Configure the connection:
- Set Transport Type to SSE
- Enter URL: http://localhost:8000/sse
- Click Connect

Test the Functions

1. Navigate to Tools section
2. Click List Tools to see available functions:
- get_alerts : Get weather alerts
- get_forcast : Get weather forecast
3. Select a function
4. Enter required parameters
5. Click Run Tool to execute

Extending the Application

Adding Custom Routes

The application structure makes it easy to add new routes:

1. Define new route handlers in routes.py
2. Add routes to the routes list in routes.py
3. The main application will automatically include these routes

Customizing MCP Integration

The MCP SSE functionality is integrated in server.py through:

- Creating an SSE transport
- Setting up an SSE handler
- Adding MCP routes to the Starlette application

Integration with Continue

To use this MCP server with the Continue VS Code extension, add the following configuration to your Continue settings:

{
  "experimental": {
    "modelContextProtocolServers": [
      {
        "transport": {
          "name": "weather",
          "type": "sse",
          "url": "http://localhost:8000/sse"
        }
      }
    ]
  }
}