loading…
Search for a command to run...
loading…
A Model Context Protocol server framework featuring dynamic tool loading and automatic tool discovery from a dedicated directory. It leverages FastMCP to provid
A Model Context Protocol server framework featuring dynamic tool loading and automatic tool discovery from a dedicated directory. It leverages FastMCP to provide a robust environment for building, configuring, and testing individual Python-based tools.
mymcpservercli is a Model Context Protocol (MCP) server built with FastMCP featuring dynamic tool loading.
src/tools/mcp.yamlsrc/
├── 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
Install Dependencies:
uv sync
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
Using uv Scripts:
# Development mode (HTTP on port 3000)
uv run dev
# HTTP mode
uv run dev-http
# Stdio mode
uv run start
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
Build Docker Image:
arctl mcp build --verbose
Run in Container:
docker run -i mymcpservercli:latest
Add New Tools:
# Create a new tool
arctl mcp add-tool weather
# Edit the tool file, then rebuild
arctl mcp build
The server supports running in HTTP mode for development and integration purposes.
# 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
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"
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)}
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
Run the generated tests to verify your tools load correctly:
uv run pytest tests/
Update pyproject.toml and run:
uv sync
uv run black .
uv run ruff check .
uv run mypy .
# Build image (handles lockfile automatically)
arctl mcp build
# Run container
docker run -i mymcpservercli:latest
Добавь это в claude_desktop_config.json и перезапусти Claude Desktop.
{
"mcpServers": {
"mymcpservercli": {
"command": "npx",
"args": []
}
}
}