FastAPI MCP SSE: Instant Data Streaming & Seamless Scaling

What is FastAPI MCP SSE: Instant Data Streaming & Seamless Scaling?

FastAPI MCP SSE is a server-side implementation leveraging the FastAPI framework and the Model Context Protocol (MCP). This integration enables real-time data streaming via Server-Sent Events (SSE) while maintaining seamless scalability. By standardizing interactions between AI models and external tools, MCP overcomes limitations such as static context boundaries and fragmented tool integration, while FastAPI ensures high-performance API handling.

How to Use FastAPI MCP SSE: Instant Data Streaming & Seamless Scaling?

Deployment begins with installing the UV Package Manager, followed by two execution options: a quick run via uvx or full installation through virtual environments. The application exposes dual endpoint categories: standard web routes (e.g., documentation, status checks) and MCP-specific SSE endpoints. Testing is streamlined using the MCP Inspector for real-time tool execution and debugging.

Key Features of FastAPI MCP SSE: Instant Data Streaming & Seamless Scaling?

• Unified Architecture: Merges MCP SSE functionality with standard FastAPI routes for cohesive API management.
• Modular Design: Segregates MCP logic from web routes using APIRouter for maintainable scalability.
• Real-Time Interactivity: SSE enables bidirectional communication for dynamic data streams without polling.
• Extensibility: Custom tools and routes can be added via Python decorators and modular configuration.

Use Cases of FastAPI MCP SSE: Instant Data Streaming & Seamless Scaling?

• Real-Time Analytics: Streaming live data feeds for adaptive decision-making systems.
• AI-Driven Chatbots: Integrating external APIs to provide up-to-date information dynamically.
• IoT Monitoring: Aggregating sensor data streams for predictive maintenance systems.
• Development Environments: Enabling tools like Continue.dev to access live model contexts for enhanced debugging.

FAQ from FastAPI MCP SSE: Instant Data Streaming & Seamless Scaling?

• Q: How does MCP enhance scalability?
  By decoupling model logic from data sources via standardized interfaces, allowing horizontal scaling of both models and tools.
• Q: Can I customize SSE event types?
  Yes, through modifying the event handler in server.py to define custom event naming conventions.
• Q: What security measures are included?
  Authentication and rate-limiting should be implemented via FastAPI middleware for production deployments.
• Q: Is this compatible with Docker?
  While not preconfigured, the modular structure allows containerization by adding a Dockerfile with the installed dependencies.

FastAPI MCP SSE

English | 简体中文

A Server-Sent Events (SSE) implementation using FastAPI 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 FastAPI web application.

Description

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

Features

• Server-Sent Events (SSE) implementation with MCP
• FastAPI 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 FastAPI application
2. Provides standard web routes (/, /about, /status, /docs, /redoc)
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/fastapi_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 FastAPI 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 (Swagger UI): http://localhost:8000/docs
  • Documentation (ReDoc): http://localhost:8000/redoc
• 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 using FastAPI's APIRouter:

1. Define new route handlers in routes.py using the APIRouter:

   @router.get("/new-route")

async def new_route():
    return {"message": "This is a new route"}

2. All routes defined with the router will be automatically included in the main application

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 FastAPI 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"
        }
      }
    ]
  }
}