developer-tools

Docker

by quantgeekdev

Manage containers with Docker and Docker Compose using natural language. Simplify your stacks with easy Docker Compose i

Manage containers and compose stacks through natural language.

github stars

455

Natural language Docker commandsFull compose stack deployment

best for

  • / Developers managing containerized applications
  • / DevOps engineers deploying multi-service stacks
  • / Anyone wanting natural language Docker control

capabilities

  • / Create standalone Docker containers
  • / Deploy Docker Compose stacks
  • / Retrieve container logs
  • / List all containers with status

what it does

Control Docker containers and compose stacks through natural language commands. Manage your Docker environment by creating containers, deploying stacks, and monitoring logs.

about

Docker is a community-built MCP server published by quantgeekdev that provides AI assistants with tools and capabilities via the Model Context Protocol. Manage containers with Docker and Docker Compose using natural language. Simplify your stacks with easy Docker Compose i It is categorized under developer tools. This server exposes 4 tools that AI clients can invoke during conversations and coding sessions.

how to install

You can install Docker in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

license

MIT

Docker is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

🐳 docker-mcp

Python 3.12 License: MIT Code style: black smithery badge

A powerful Model Context Protocol (MCP) server for Docker operations, enabling seamless container and compose stack management through Claude AI.

✨ Features

  • 🚀 Container creation and instantiation
  • 📦 Docker Compose stack deployment
  • 🔍 Container logs retrieval
  • 📊 Container listing and status monitoring

🎬 Demos

Deploying a Docker Compose Stack

https://github.com/user-attachments/assets/b5f6e40a-542b-4a39-ba12-7fdf803ee278

Analyzing Container Logs

https://github.com/user-attachments/assets/da386eea-2fab-4835-82ae-896de955d934

🚀 Quickstart

To try this in Claude Desktop app, add this to your claude config files:

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

Installing via Smithery

To install Docker MCP for Claude Desktop automatically via Smithery:

npx @smithery/cli install docker-mcp --client claude

Prerequisites

  • UV (package manager)
  • Python 3.12+
  • Docker Desktop or Docker Engine
  • Claude Desktop

Installation

Claude Desktop Configuration

Add the server configuration to your Claude Desktop config file:

MacOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json
Windows: %APPDATA%/Claude/claude_desktop_config.json

<details> <summary>💻 Development Configuration</summary>
{
  "mcpServers": {
    "docker-mcp": {
      "command": "uv",
      "args": [
        "--directory",
        "<path-to-docker-mcp>",
        "run",
        "docker-mcp"
      ]
    }
  }
}
</details> <details> <summary>🚀 Production Configuration</summary>
{
  "mcpServers": {
    "docker-mcp": {
      "command": "uvx",
      "args": [
        "docker-mcp"
      ]
    }
  }
}
</details>

🛠️ Development

Local Setup

  1. Clone the repository:
git clone https://github.com/QuantGeekDev/docker-mcp.git
cd docker-mcp
  1. Create and activate a virtual environment:
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate
  1. Install dependencies:
uv sync

🔍 Debugging

Launch the MCP Inspector for debugging:

npx @modelcontextprotocol/inspector uv --directory <path-to-docker-mcp> run docker-mcp

The Inspector will provide a URL to access the debugging interface.

📝 Available Tools

The server provides the following tools:

create-container

Creates a standalone Docker container

{
    "image": "image-name",
    "name": "container-name",
    "ports": {"80": "80"},
    "environment": {"ENV_VAR": "value"}
}

deploy-compose

Deploys a Docker Compose stack

{
    "project_name": "example-stack",
    "compose_yaml": "version: '3.8'
services:
  service1:
    image: image1:latest
    ports:
      - '8080:80'"
}

get-logs

Retrieves logs from a specific container

{
    "container_name": "my-container"
}

list-containers

Lists all Docker containers

{}

🚧 Current Limitations

  • No built-in environment variable support for containers
  • No volume management
  • No network management
  • No container health checks
  • No container restart policies
  • No container resource limits

🤝 Contributing

  1. Fork the repository from docker-mcp
  2. Create your feature branch
  3. Commit your changes
  4. Push to the branch
  5. Open a Pull Request

📜 License

This project is licensed under the MIT License - see the LICENSE file for details.

✨ Authors

  • Alex Andru - Initial work | Core contributor - @QuantGeekDev
  • Ali Sadykov - Initial work | Core contributor - @md-archive

Made with ❤️

FAQ

What is the Docker MCP server?
Docker is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for Docker?
This profile displays 10 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.5 out of 5—verify behavior in your own environment before production use.
MCP server reviews

Ratings

4.510 reviews
  • Shikha Mishra· Oct 10, 2024

    Docker is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • Piyush G· Sep 9, 2024

    We evaluated Docker against two servers with overlapping tools; this profile had the clearer scope statement.

  • Chaitanya Patil· Aug 8, 2024

    Useful MCP listing: Docker is the kind of server we cite when onboarding engineers to host + tool permissions.

  • Sakshi Patil· Jul 7, 2024

    Docker reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

  • Ganesh Mohane· Jun 6, 2024

    I recommend Docker for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Oshnikdeep· May 5, 2024

    Strong directory entry: Docker surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • Dhruvi Jain· Apr 4, 2024

    Docker has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Rahul Santra· Mar 3, 2024

    According to our notes, Docker benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Pratham Ware· Feb 2, 2024

    We wired Docker into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

  • Yash Thakker· Jan 1, 2024

    Docker is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.