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mcp-digitalocean-server

MCP.Pizza Chef: luc-io

The mcp-digitalocean-server is an MCP server implementation that integrates with DigitalOcean's API to enable cloud server management through the Model Context Protocol. It provides a FastAPI-based HTTP server that allows LLMs and clients to interact with DigitalOcean resources securely and efficiently, facilitating real-time server operations and context sharing within AI workflows.

Use This MCP server To

Manage DigitalOcean droplets via MCP protocol Automate cloud server provisioning and scaling Retrieve DigitalOcean server status and metrics Integrate DigitalOcean server data into AI workflows Trigger server actions from natural language commands Monitor DigitalOcean resources in real-time Enable LLMs to control cloud infrastructure Facilitate DevOps automation with DigitalOcean API

README

MCP DigitalOcean Server

A Model Context Protocol implementation that integrates with DigitalOcean for server management.

Setup

  1. Clone this repository
  2. Copy .env.example to .env and fill in your DigitalOcean API token
  3. Install dependencies: 
    pip install -r requirements.txt
  4. Run the server: 
    python src/server.py

Features

  • MCP Protocol implementation
  • DigitalOcean integration for server management
  • FastAPI-based HTTP server

Configuration

Configure the following environment variables in your .env file:

  • DIGITALOCEAN_TOKEN: Your DigitalOcean API token
  • MCP_SERVER_PORT: Port for the MCP server (default: 8000)
  • MCP_SERVER_HOST: Host for the MCP server (default: 0.0.0.0)

mcp-digitalocean-server FAQ

How do I configure the DigitalOcean API token for this MCP server?
Set your DigitalOcean API token in the `DIGITALOCEAN_TOKEN` environment variable in the `.env` file before running the server.
What framework does the mcp-digitalocean-server use?
It uses FastAPI to provide a lightweight, asynchronous HTTP server for MCP interactions.
Can this MCP server handle multiple DigitalOcean resources?
Yes, it supports managing multiple droplets and other DigitalOcean resources through the MCP interface.
Is the mcp-digitalocean-server compatible with different LLM providers?
Yes, it is provider-agnostic and works with OpenAI, Claude, Gemini, and others supporting MCP.
How do I start the mcp-digitalocean-server after setup?
After installing dependencies and configuring `.env`, run `python src/server.py` to start the server.
Can I customize the server host and port?
Yes, configure `MCP_SERVER_HOST` and `MCP_SERVER_PORT` environment variables to set host and port.
Does this server support secure interactions?
Security depends on your environment setup; use secure tokens and network configurations to protect API access.
What kind of DigitalOcean operations can be performed?
Operations include creating, deleting, and managing droplets, retrieving server info, and monitoring resource status.