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Skeleton MCP Server

by nickweedon

Skeleton MCP Server

A template project for building Model Context Protocol (MCP) servers. This skeleton provides a solid foundation with best practices, Docker support, and example implementations.

Features

  • FastMCP framework for easy MCP server development

  • Docker and Docker Compose support for containerized deployment

  • VS Code Dev Container configuration for consistent development environments

  • Example CRUD API implementation to demonstrate patterns

  • Test suite with pytest

  • Claude Code integration with custom commands

Quick Start

Prerequisites

  • Python 3.10 or higher

  • uv package manager (recommended)

  • Docker (optional, for containerized deployment)

Installation

  1. Clone this repository and rename it for your project:

git clone <this-repo> my-mcp-server
cd my-mcp-server
  1. Rename the package:

    • Rename src/skeleton_mcp to src/your_project_name

    • Update pyproject.toml with your project name and metadata

    • Update imports in all Python files

  2. Install dependencies:

uv sync
  1. Create your environment file:

cp .env.example .env
# Edit .env with your API credentials
  1. Run the server:

uv run skeleton-mcp

Project Structure

skeleton_mcp/
├── src/skeleton_mcp/
│   ├── __init__.py          # Package initialization
│   ├── server.py            # Main MCP server entry point
│   ├── client.py            # API client for backend communication
│   ├── types.py             # TypedDict definitions
│   ├── api/                  # API modules
│   │   ├── __init__.py
│   │   └── example.py       # Example CRUD operations
│   └── utils/               # Utility modules
│       └── __init__.py
├── tests/                   # Test suite
│   ├── conftest.py          # Pytest fixtures
│   ├── test_example_api.py  # API tests
│   └── test_server.py       # Server tests
├── docs/                    # Documentation
├── .claude/                 # Claude Code configuration
│   ├── commands/            # Custom slash commands
│   └── settings.local.json  # Permission settings
├── .devcontainer/           # VS Code dev container
├── Dockerfile               # Container image definition
├── docker-compose.yml       # Production compose file
├── docker-compose.devcontainer.yml  # Dev container compose
├── pyproject.toml           # Project configuration
├── CLAUDE.md               # Claude context documentation
└── README.md               # This file

Development

Running Tests

uv run pytest -v

Linting

uv run ruff check src/ tests/
uv run ruff format src/ tests/

Building

uv build

Adding Your Own Tools

  1. Create a new module in src/skeleton_mcp/api/:

# src/skeleton_mcp/api/my_api.py

async def my_tool(param1: str, param2: int = 10) -> dict:
    """
    Description of what this tool does.

    Args:
        param1: Description of param1
        param2: Description of param2

    Returns:
        Description of return value
    """
    # Your implementation here
    return {"result": "success"}
  1. Register the tool in server.py:

from .api import my_api

mcp.tool()(my_api.my_tool)
  1. Add types in types.py if needed:

class MyDataType(TypedDict):
    field1: str
    field2: int

Handling Large Files and Binary Data

For MCP servers that need to handle large file uploads, downloads, or binary blob storage, use the mcp-mapped-resource-lib library:

pip install mcp-mapped-resource-lib

This library provides:

  • Blob management with unique identifiers

  • Automatic TTL-based expiration and cleanup

  • Content deduplication

  • Security features (path traversal prevention, MIME validation)

  • Docker volume integration for shared storage

See CLAUDE.md for detailed usage examples.

Docker Deployment

Build and run with Docker Compose:

docker compose up --build

For development with VS Code Dev Containers:

  1. Open the project in VS Code

  2. Install the "Dev Containers" extension

  3. Click "Reopen in Container" when prompted

Claude Desktop Integration

Add to your Claude Desktop configuration (claude_desktop_config.json):

{
  "mcpServers": {
    "skeleton-mcp": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "--env-file",
        "/path/to/your/.env",
        "skeleton-mcp:latest"
      ]
    }
  }
}

Or for local development:

{
  "mcpServers": {
    "skeleton-mcp": {
      "command": "uv",
      "args": ["--directory", "/path/to/skeleton_mcp", "run", "skeleton-mcp"]
    }
  }
}

Available Tools

Tool

Description

health_check

Check server health and configuration status

list_items

List all items with filtering and pagination

get_item

Get a specific item by ID

create_item

Create a new item

update_item

Update an existing item

delete_item

Delete an item

Environment Variables

Variable

Description

Default

API_KEY

Your API key for authentication

(required)

API_BASE_URL

Base URL for the backend API

https://api.example.com/v1

API_TIMEOUT

Request timeout in seconds

30

DEBUG

Enable debug logging

false

License

MIT License - See LICENSE file for details.

Contributing

  1. Fork the repository

  2. Create a feature branch

  3. Make your changes

  4. Run tests and linting

  5. Submit a pull request

Install Server
A
security – no known vulnerabilities
F
license - not found
A
quality - confirmed to work

Resources

Looking for Admin?

Admins can modify the Dockerfile, update the server description, and track usage metrics. If you are the server author, to access the admin panel.

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