Provides tools for managing Docker containers, images, Dockerfiles, and Docker Compose configurations, enabling AI agents to list containers and images, analyze Dockerfiles for best practices, analyze Compose files, and retrieve container logs.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@mcp-docker-tools list all running containers"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Docker management tools for AI agents, built on the Model Context Protocol.
Provides five tools for inspecting containers, images, Dockerfiles, and Compose configurations — all accessible to LLMs through MCP.
Tool | Description |
| List running or all containers with status, ports, image, created time, and resource usage (CPU, memory, network/block I/O) |
| List Docker images with size, tags, created date, and layer count |
| Analyze a Dockerfile for best practices: multi-stage builds, non-root user, layer caching, image size, security |
| Analyze docker-compose.yml: services, ports, volumes, networks, health checks, dependencies, and improvement suggestions |
| Get container logs with tail, keyword filter, time range, and timestamp support |
Related MCP server: mcp-server-docker
Node.js >= 18
Docker CLI installed and accessible in PATH
Docker daemon running (for container/image tools)
git clone <repo-url>
cd mcp-docker-tools
npm install
npm run buildAdd to your Claude Desktop configuration (claude_desktop_config.json):
{
"mcpServers": {
"docker-tools": {
"command": "node",
"args": ["D:/products/mcp-servers/mcp-docker-tools/dist/index.js"]
}
}
}claude mcp add docker-tools node D:/products/mcp-servers/mcp-docker-tools/dist/index.jsOr add to .claude/settings.json:
{
"mcpServers": {
"docker-tools": {
"command": "node",
"args": ["D:/products/mcp-servers/mcp-docker-tools/dist/index.js"]
}
}
}{ "tool": "docker_container_list" }{ "tool": "docker_container_list", "args": { "all": true, "format": "table" } }{ "tool": "docker_image_list", "args": { "filter": "node" } }{
"tool": "docker_dockerfile_analyze",
"args": {
"content": "FROM node:20\nCOPY . .\nRUN npm install\nCMD [\"node\", \"index.js\"]"
}
}{
"tool": "docker_compose_analyze",
"args": {
"content": "services:\n web:\n image: nginx\n ports:\n - 80:80"
}
}{
"tool": "docker_container_logs",
"args": { "container": "my-app", "tail": 50, "filter": "error" }
}MIT
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Provides capabilities that let LLM agents perform a range of infrastructure management tasks.
Manage portable AI agent playbooks, Agent Skills, MCP configurations, personas, and memory.
A registry of AI agent tools — MCP servers, APIs, CLIs, SDKs — kept current by automated ingestion.
Machine-readable utilities and datasets for AI agents.
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/rog0x/mcp-docker-tools'
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