Demo 🚀 Service Documentation
License
🌟 Project Overview
This project implements a Model Control Protocol service based on the FastMCP framework, providing:

• Synchronous tool invocation: Implements addition calculation functionality
• Dynamic resource routing: Supports personalized greeting generation
• Standard protocol support: Complies with the Model Control Protocol specification

🧠 Technical Architecture
mermaid
graph TD
A[Client] -->|HTTP/WebSocket| B(FastMCP Service)
B --> C{Function Modules}
C --> D[Tool Invocation]
C --> E[Resource Routing]
D --> F[add function]
E --> G[greeting resource]
B --> H[Pydantic Data Validation]
B --> I[SSE Streaming Response]

🛠️ Environment Requirements
Component Version Requirement
Python 3.10+
FastMCP 0.1.0+
Pydantic 2.0.0+
Uvicorn 0.22.0+

📦 Installation Guide
bash

Create a virtual environment

python -m venv venv
source venv/bin/activate

Install dependencies

pip install fastmcp pydantic uvicorn sse-starlette

🚀 Quick Start
bash

Start the service (stdio mode)

python main.py

Or start using Uvicorn (recommended for production)

uvicorn main:app --reload

🧩 Core Features

1. Tool Invocation add
   python
   @mcp.tool()
   def add(a: int, b: int) -> int:
   """Add two numbers"""
   return a + b

Invocation Example:
json
{
"method": "add",
"params": {"a": 2, "b": 3},
"response": 5
}

1. Dynamic Resource greeting://{name}
   python
   @mcp.resource("greeting://{name}")
   def get_greeting(name: str) -> str:
   """Get a personalized greeting"""
   return f"Hello, {name}!"

Access Example:
bash
GET /greeting://Alice

Returns: "Hello, Alice!"

📡 API Specification
Tool Invocation Interface
Method: POST /tool_call
Request Body:
json
{
"method": "add",
"params": {"a": 2, "b": 3}
}

Response:
json
{
"result": 5
}

Resource Access Interface
Method: GET /greeting://{name}
Path Parameters:

• name: The name to be greeted

🛡️ Service Deployment
Production Environment Configuration
bash

Deploy using Uvicorn

uvicorn main:app --host 0.0.0.0 --port 8000 --workers 4

Docker Deployment Example
dockerfile
FROM python:3.10-slim
WORKDIR /app
COPY . .
RUN pip install -r requirements.txt
CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000"]

📐 Development Guidelines

• Type Annotations: All functions must use Python type annotations.
• Docstrings: Each tool/resource must include a docstring description.
• Exception Handling: Use PydanticCustomError for error handling.
• Logging: Use the standard logging module to output logs.
• Code Style: Follow PEP8 guidelines.

🤝 Contributing

• Fork the repository
• Create a feature branch git checkout -b feature/xxx
• Commit your changes git commit -am 'Add xxx'
• Push the branch git push origin feature/xxx
• Create a PR and attach a description of the changes

📄 License
MIT License (to be replaced with the actual license)

📌 Notes
For production environments, it is necessary to add:

• JWT authentication
• Request rate limiting strategies
• Prometheus monitoring metrics
• Distributed tracing support
• Fault tolerance mechanisms

The service uses stdio communication by default. It is recommended to switch to HTTP mode in production environments:
python
if name == "main":
mcp.run(transport="http", port=8000)