My MCP Server

1

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claude mcp add my-mcp-server -- docker run -i my-mcp-server:latest
README.md

An MCP server with dynamic tool loading and configuration from Python files.

my-mcp-server

my-mcp-server is a Model Context Protocol (MCP) server built with FastMCP featuring dynamic tool loading.

Features

  • Dynamic Tool Loading: Tools are automatically discovered and loaded from src/tools/
  • One Tool Per File: Each tool is a single file with a function matching the filename
  • FastMCP Integration: Leverages FastMCP for robust MCP protocol handling
  • Configuration Management: Tool-specific configuration via mcp.yaml
  • Fail-Fast: Server won't start if any tool fails to load
  • Auto-Generated Tests: Automatic test generation for tool validation

Project Structure

src/
├── tools/              # Tool implementations (one file per tool)
│   ├── echo.py         # Example echo tool
│   └── __init__.py     # Auto-generated tool registry
├── core/               # Dynamic loading framework
│   ├── server.py       # Dynamic MCP server
│   └── utils.py        # Shared utilities
└── main.py             # Entry point
mcp.yaml               # Configuration file
tests/                  # Generated tests

Quick Start

Option 1: Local Development (with Python/uv)

  1. Install Dependencies:

    uv sync
    
  2. Run the Server:

    # Stdio mode (default MCP transport)
    uv run python src/main.py
    
    # HTTP mode with WebSocket MCP endpoint
    uv run python src/main.py --http
    
    # HTTP mode with custom host/port
    uv run python src/main.py --http --host 0.0.0.0 --port 8080
    
  3. Using uv Scripts:

    # Development mode (HTTP on port 3000)
    uv run dev
    
    # HTTP mode
    uv run dev-http
    
    # Stdio mode
    uv run start
    
  4. Add New Tools:

    # Create a new tool (no tool types needed!)
    arctl mcp add-tool weather
    
    # The tool file will be created at src/tools/weather.py
    # Edit it to implement your tool logic
    

Option 2: Docker-Only Development (no local Python/uv required)

  1. Build Docker Image:

    arctl mcp build --verbose
    
  2. Run in Container:

    docker run -i my-mcp-server:latest
    
  3. Add New Tools:

    # Create a new tool
    arctl mcp add-tool weather
    
    # Edit the tool file, then rebuild
    arctl mcp build
    

HTTP Transport Mode

The server supports running in HTTP mode for development and integration purposes.

Starting in HTTP Mode

# Command line flag
python src/main.py --http

# Environment variable
MCP_TRANSPORT_MODE=http python src/main.py

# Custom host and port
python src/main.py --http --host localhost --port 8080

Creating Tools

Basic Tool Structure

Each tool is a Python file in src/tools/ containing a function decorated with @mcp.tool():

# src/tools/weather.py
from core.server import mcp
from core.utils import get_tool_config, get_env_var

@mcp.tool()
def weather(location: str) -> str:
    """Get weather information for a location."""
    
    # Get tool configuration
    config = get_tool_config("weather")
    api_key = get_env_var(config.get("api_key_env", "WEATHER_API_KEY"))
    base_url = config.get("base_url", "https://api.openweathermap.org/data/2.5")
    
    # TODO: Implement weather API call
    return f"Weather for {location}: Sunny, 72°F"

Tool Examples

The generated tool template includes commented examples for common patterns:

# HTTP API calls
# async with httpx.AsyncClient() as client:
#     response = await client.get(f"{base_url}/weather?q={location}&appid={api_key}")
#     return response.json()

# Database operations  
# async with asyncpg.connect(connection_string) as conn:
#     result = await conn.fetchrow("SELECT * FROM weather WHERE location = $1", location)
#     return dict(result)

# File processing
# with open(file_path, 'r') as f:
#     content = f.read()
#     return {"content": content, "size": len(content)}

Configuration

Configure tools in mcp.yaml:

tools:
  weather:
    api_key_env: "WEATHER_API_KEY"
    base_url: "https://api.openweathermap.org/data/2.5"
    timeout: 30
  
  database:
    connection_string_env: "DATABASE_URL"
    max_connections: 10

Testing

Run the generated tests to verify your tools load correctly:

uv run pytest tests/

Development

Adding Dependencies

Update pyproject.toml and run:

uv sync

Code Quality

uv run black .
uv run ruff check .
uv run mypy .

Deployment

Docker

# Build image (handles lockfile automatically)
arctl mcp build

# Run container
docker run -i my-mcp-server:latest

Tools (1)

weatherGet weather information for a location.

Environment Variables

MCP_TRANSPORT_MODESets the transport mode (e.g., http)
WEATHER_API_KEYAPI key for weather tool integration
DATABASE_URLConnection string for database tool integration

Configuration

claude_desktop_config.json
{"mcpServers": {"my-mcp-server": {"command": "uv", "args": ["run", "src/main.py"]}}}

Try it

What is the current weather in London?
Can you check the weather for Tokyo using the weather tool?
Fetch the latest data from the database using the configured connection.

Frequently Asked Questions

What are the key features of My MCP Server?

Dynamic tool loading from individual Python files in src/tools/. FastMCP integration for robust protocol handling. Automatic test generation for tool validation. Flexible configuration management via mcp.yaml. Support for both Stdio and HTTP transport modes.

What can I use My MCP Server for?

Rapidly prototyping new AI tools without modifying core server code. Managing tool-specific configurations in a centralized YAML file. Automating the testing and validation of custom MCP tools. Deploying modular AI toolsets in containerized environments.

How do I install My MCP Server?

Install My MCP Server by running: uv sync && uv run python src/main.py

What MCP clients work with My MCP Server?

My MCP Server works with any MCP-compatible client including Claude Desktop, Claude Code, Cursor, and other editors with MCP support.

Turn this server into reusable context

Keep My MCP Server docs, env vars, and workflow notes in Conare so your agent carries them across sessions.

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