MCP Python Starter

MCP Python Starter

A feature-complete Model Context Protocol (MCP) server template in Python using FastMCP. This starter demonstrates all major MCP features with clean, Pythonic code.

📚 Documentation

• Model Context Protocol
• Python SDK
• FastMCP Guide

✨ Features

Category	Feature	Description
Tools	hello	Basic tool with annotations
	get_weather	Tool returning structured data
	ask_llm	Tool that invokes LLM sampling
	long_task	Tool with 5-second progress updates
	load_bonus_tool	Dynamically loads a new tool
Resources	info://about	Static informational resource
	file://example.md	File-based markdown resource
Templates	greeting://{name}	Personalized greeting
	data://items/{id}	Data lookup by ID
Prompts	greet	Greeting in various styles
	code_review	Code review with focus areas

🚀 Quick Start

Prerequisites

• Python 3.11+
• uv (recommended) or pip

Installation

# Clone the repository
git clone https://github.com/SamMorrowDrums/mcp-python-starter.git
cd mcp-python-starter

# Install with uv (recommended)
uv sync

# Or with pip
pip install -e .

Running the Server

stdio transport (for local development):

uv run mcp-python-starter --stdio

HTTP transport (for remote/web deployment):

uv run mcp-python-starter --http --port 3000

🔧 VS Code Integration

This project includes VS Code configuration for seamless development:

1. Open the project in VS Code
2. The MCP configuration is in .vscode/mcp.json
3. Test the server using VS Code's MCP tools

Using DevContainers

1. Install the Dev Containers extension
2. Open command palette: "Dev Containers: Reopen in Container"
3. Everything is pre-configured and ready to use!

📁 Project Structure

.
├── mcp_starter/
│   ├── __init__.py
│   ├── tools.py       # Tool definitions (hello, get_weather, ask_llm, etc.)
│   ├── resources.py   # Resource and template definitions
│   ├── prompts.py     # Prompt definitions
│   └── server.py      # Server orchestration (imports and wires modules)
├── .vscode/
│   ├── mcp.json       # MCP server configuration
│   ├── settings.json  # Python settings
│   └── extensions.json
├── .devcontainer/
│   └── devcontainer.json
├── pyproject.toml     # Project configuration (uv/pip, Ruff config)
└── .python-version

🛠️ Development

# Run the server (Python reloads automatically on changes)
uv run mcp-python-starter --stdio

# Use MCP Inspector for debugging
uv run mcp dev mcp_starter/server.py

# Format code
uv run ruff format .

# Lint
uv run ruff check .

# Lint with auto-fix
uv run ruff check --fix .

# Type check
uv run pyright

Live Reload

Python scripts reload automatically when run with uv run. For enhanced debugging, use mcp dev which provides the MCP Inspector UI.

🔍 MCP Inspector

The MCP Inspector is an essential development tool for testing and debugging MCP servers.

Running Inspector

npx @modelcontextprotocol/inspector -- uv run mcp-python-starter

What Inspector Provides

• Tools Tab: List and invoke all registered tools with parameters
• Resources Tab: Browse and read resources and templates
• Prompts Tab: View and test prompt templates
• Logs Tab: See JSON-RPC messages between client and server
• Schema Validation: Verify tool input/output schemas

Debugging Tips

1. Start Inspector before connecting your IDE/client
2. Use the "Logs" tab to see exact request/response payloads
3. Test tool annotations (ToolAnnotations) are exposed correctly
4. Verify progress notifications appear for long_task
5. Check that Context injection works for sampling tools

📖 Feature Examples

Tool with Annotations (FastMCP decorator)

@mcp.tool(
    title="Say Hello",
    description="A friendly greeting tool",
    annotations={"readOnlyHint": True},
)
def hello(name: str) -> str:
    """Say hello to someone.
    
    Args:
        name: The name to greet
    """
    return f"Hello, {name}!"

Resource Template

@mcp.resource("greeting://{name}")
def greeting_template(name: str) -> str:
    """Generate a personalized greeting."""
    return f"Hello, {name}!"

Tool with Progress Updates

@mcp.tool(title="Long Task")
async def long_task(
    task_name: str,
    ctx: Context[ServerSession, None],
) -> str:
    for i in range(5):
        await ctx.report_progress(
            progress=i / 5,
            total=1.0,
            message=f"Step {i + 1}/5",
        )
        await asyncio.sleep(1.0)
    return "Done!"

Tool with Sampling

@mcp.tool(title="Ask LLM")
async def ask_llm(
    prompt: str,
    ctx: Context[ServerSession, None],
) -> str:
    result = await ctx.session.create_message(
        messages=[{"role": "user", "content": {"type": "text", "text": prompt}}],
        max_tokens=100,
    )
    return result.content.text

🔐 Environment Variables

Copy .env.example to .env and configure:

cp .env.example .env

🤝 Contributing

Contributions welcome! Please ensure your changes maintain feature parity with other language starters.

📄 License

MIT License - see LICENSE for details.