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MCP server for Docker, DigitalOcean, and CloudFlare operations

Project description

CargoShipper MCP Server

Python 3.11+ MCP PyPI uvx

A comprehensive MCP (Model Context Protocol) server that provides Claude with direct access to Docker, DigitalOcean, and CloudFlare APIs for infrastructure management and automation.

โš ๏ธ IMPORTANT SAFETY WARNING

USE AT YOUR OWN RISK: This tool gives AI models direct access to infrastructure management APIs that can:

  • Create, modify, or delete cloud resources (potentially incurring costs)
  • Modify DNS settings (potentially breaking domains)
  • Manage Docker containers and images (potentially affecting running services)
  • Execute destructive operations on your infrastructure

Before using:

  • Ensure you understand the capabilities and risks of each API
  • Start with non-production environments only
  • Review all operations before execution in production
  • Monitor costs and resource usage carefully
  • Have backup and recovery procedures in place

AI models may:

  • Misinterpret instructions and perform unintended operations
  • Make mistakes in resource configuration or deletion
  • Execute multiple operations when only one was intended
  • Struggle with complex multi-step procedures requiring human judgment

Recommended safety measures:

  • Use dedicated development/testing accounts with spending limits
  • Implement least-privilege API tokens with restricted permissions
  • Monitor all operations through cloud provider dashboards
  • Test operations in isolated environments first
  • Keep backups of critical configurations and data

๐Ÿค– VIBECODE FRIENDLY PROJECT

This project welcomes contributions from AI/LLM agents! Pull requests from Claude, GPT, and other AI models are actively encouraged.

Guidelines for AI contributors:

  • Follow existing code patterns and documentation standards
  • Include comprehensive commit messages explaining changes
  • Test changes thoroughly before submitting PRs
  • Update documentation when adding new features

โœจ Easy Setup with uvx

CargoShipper is available on PyPI and works seamlessly with uvx for easy installation and management, just like mcp-server-git.

Quick Install from PyPI

# Run directly (recommended)
uvx cargoshipper-mcp

# Configure in your .mcp.json
{
  "mcpServers": {
    "cargoshipper": {
      "command": "uvx",
      "args": ["cargoshipper-mcp"]
    }
  }
}

Development Setup

For local development and testing:

  1. Clone the repository:

    cd cargoshipper-mcp
    
  2. Install dependencies:

    pip install -r requirements.txt
    # or create a virtual environment first
    python3 -m venv .venv
    source .venv/bin/activate  # Linux/Mac
    pip install -r requirements.txt
    
  3. Configure your APIs:

    cp .env.example .env
    # Edit .env with your API tokens:
    # DIGITALOCEAN_TOKEN=your_token_here
    # CLOUDFLARE_API_TOKEN=your_token_here
    
  4. Use the development MCP configuration:

    # Use .mcp.dev.json for local development
    cp .mcp.dev.json .mcp.json
    

๐Ÿณ Docker Integration

  • Container Management: Full lifecycle (create, start, stop, remove, logs)
  • Image Operations: List, pull, and manage Docker images
  • System Information: Docker system stats and health
  • Resource Monitoring: Container resource usage and status

๐ŸŒŠ DigitalOcean Integration

  • Droplet Management: Complete droplet lifecycle management
  • DNS Management: Full DNS record CRUD operations
  • Account Information: Access account details and billing
  • Image Management: Work with distributions and custom snapshots

โ˜๏ธ CloudFlare Integration

  • Zone Management: Create and configure CloudFlare zones
  • DNS Operations: Advanced DNS with proxy settings
  • Cache Control: Purge cache by URL, tags, or everything
  • Analytics: Traffic and performance analytics
  • Security Settings: SSL, security levels, firewall rules

๐Ÿ”ง Available Tools & Resources

30 Tools Total:

  • Docker (9 tools): docker_run_container, docker_list_containers, etc.
  • DigitalOcean (10 tools): do_create_droplet, do_list_dns_records, etc.
  • CloudFlare (11 tools): cf_create_zone, cf_purge_cache, etc.

17 Resources Total:

  • docker://containers - All containers with status
  • digitalocean://droplets - All droplets with costs
  • cloudflare://zones - All zones with analytics
  • And many more...

๐Ÿ“‹ Configuration Files

Production (.mcp.json)

{
  "mcpServers": {
    "cargoshipper": {
      "command": "uvx", 
      "args": ["cargoshipper-mcp"]
    }
  }
}

Development (.mcp.dev.json)

{
  "mcpServers": {
    "cargoshipper": {
      "command": "python",
      "args": ["-m", "cargoshipper_mcp.server"],
      "cwd": ".",
      "env": {
        "PYTHONPATH": "."
      }
    }
  }
}

๐Ÿ”‘ API Credentials Setup

Create .env file or ~/.config/cargoshipper-mcp/.env:

# DigitalOcean API Token
DIGITALOCEAN_TOKEN=your_digitalocean_token_here

# CloudFlare API Token (recommended)
CLOUDFLARE_API_TOKEN=your_cloudflare_token_here

# Alternative: CloudFlare Email + Global API Key
# CLOUDFLARE_EMAIL=your@email.com
# CLOUDFLARE_API_KEY=your_global_api_key

Getting API Tokens:

๐Ÿš€ Usage Examples

Once configured, Claude will have access to infrastructure operations:

# Docker examples
"Run an nginx container on port 8080"
"List all running containers"
"Get logs from container abc123"

# DigitalOcean examples  
"Create a small droplet in NYC3"
"List all my droplets and their costs"
"Add an A record for api.example.com"

# CloudFlare examples
"Create a new zone for mysite.com"
"Purge all cache for example.com" 
"Show me analytics for the last 24 hours"

๐Ÿ“ Project Structure

cargoshipper-mcp/
โ”œโ”€โ”€ cargoshipper_mcp/        # Main package (renamed from src/)
โ”‚   โ”œโ”€โ”€ server.py           # MCP server entry point  
โ”‚   โ”œโ”€โ”€ config/             # Configuration with multi-path .env loading
โ”‚   โ”œโ”€โ”€ tools/              # API operation tools
โ”‚   โ”‚   โ”œโ”€โ”€ docker.py       # Docker operations
โ”‚   โ”‚   โ”œโ”€โ”€ digitalocean.py # DigitalOcean operations
โ”‚   โ”‚   โ””โ”€โ”€ cloudflare.py   # CloudFlare operations
โ”‚   โ”œโ”€โ”€ resources/          # Read-only data access
โ”‚   โ””โ”€โ”€ utils/              # Shared utilities
โ”œโ”€โ”€ .mcp.json              # Production MCP config (uvx)
โ”œโ”€โ”€ .mcp.dev.json          # Development MCP config (local python)
โ”œโ”€โ”€ pyproject.toml         # Python packaging (uvx compatible)
โ”œโ”€โ”€ requirements.txt       # Dependencies
โ””โ”€โ”€ install.sh             # uvx installation script

๐ŸŒ Published on PyPI

CargoShipper MCP is now available on PyPI! Access it at: https://pypi.org/project/cargoshipper-mcp/

Setup is as simple as:

# Run directly (most common)
uvx cargoshipper-mcp

# Configure in .mcp.json
{
  "mcpServers": {
    "cargoshipper": {
      "command": "uvx",
      "args": ["cargoshipper-mcp"] 
    }
  }
}

๐Ÿ› ๏ธ Development

Package Structure

  • Uses proper Python packaging with pyproject.toml
  • Console entry point: cargoshipper-mcp = "cargoshipper_mcp.server:main"
  • Multi-path environment loading for uvx compatibility
  • Type hints and comprehensive error handling throughout

Testing

python test_server.py  # Validates imports and configuration

This approach follows the same pattern as mcp-server-git and other uvx-compatible MCP servers, making it extremely easy to install and use once published!

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