Docker MCP: Bridge Your Docker Workflow with Claude AI

Stop context-switching between Claude conversations and terminal windows. docker-mcp lets you manage Docker containers and compose stacks directly through Claude AI, turning your AI assistant into a powerful Docker orchestration tool.

The Problem with Traditional Docker + AI Workflows

You're debugging an application in Claude, discussing architecture and troubleshooting issues. Then you need to:

• Switch to terminal to check container logs
• Deploy a new compose stack to test a solution
• Copy-paste logs back to Claude for analysis
• Repeat this dance dozens of times per debugging session

Every context switch kills your flow and fragments your problem-solving process.

Direct Docker Control from Claude

docker-mcp eliminates the friction by giving Claude direct access to your Docker environment. Ask Claude to "check the logs for my web container" or "deploy this compose stack" and it happens instantly - no terminal switching required.

Real Productivity Gains

Streamlined Debugging: Analyze application logs without leaving your Claude conversation. Claude can examine error patterns, suggest fixes, and even deploy test environments to validate solutions.

Rapid Prototyping: Describe what you want to test, and Claude can spin up the entire Docker environment. Need a Redis cache for testing? Claude deploys it and integrates it into your existing stack.

Environment Troubleshooting: When something breaks, Claude can check container status, pull logs, and correlate issues across your entire stack - all while maintaining context of your original problem.

Four Essential Tools, Maximum Impact

create-container: Deploy standalone containers with custom configurations

{
    "image": "redis:alpine",
    "name": "test-cache",
    "ports": {"6379": "6379"},
    "environment": {"REDIS_PASSWORD": "dev-password"}
}

deploy-compose: Launch complete application stacks from YAML

{
    "project_name": "microservices-test",
    "compose_yaml": "version: '3.8'\nservices:\n  api:\n    image: my-api:latest\n    ports:\n      - '3000:3000'"
}

get-logs: Retrieve container logs for analysis

{
    "container_name": "failing-service"
}

list-containers: Get complete container status overview

{}

Perfect for Development Workflows

Local Development: Test different configurations and architectures without memorizing Docker commands. Claude understands your requirements and translates them into proper container deployments.

Debugging Sessions: When production issues surface, Claude can recreate similar environments locally, pull relevant logs, and help you trace problems across multiple containers.

Learning and Experimentation: Try new technologies without Docker expertise. Describe what you want to test, and Claude handles the container orchestration while explaining what it's doing.

Installation Takes 30 Seconds

Add to your Claude Desktop config:

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

Or use Smithery for automatic setup:

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

Requires Docker Desktop and Python 3.12+. That's it.

Integration That Makes Sense

docker-mcp doesn't replace your existing Docker workflow - it enhances it. Use it when you need AI-assisted container management, fall back to terminal commands when you need advanced Docker features not yet supported.

The MCP protocol ensures reliable communication between Claude and your Docker daemon, with proper error handling and status reporting. Your containers run exactly as they would with direct Docker commands.

Ready to stop switching contexts and start managing Docker through Claude? docker-mcp transforms your AI assistant into a capable DevOps partner, keeping you in the flow while handling the container orchestration details.