mcp-server-k8s: A Kubernetes MCP Server

The Model Context Protocol (MCP) is an open protocol that enables seamless integration between LLM applications and external data sources and tools. Whether you're building an AI-powered IDE, enhancing a chat interface, or creating custom AI workflows, MCP provides a standardized way to connect LLMs with the context they need.

This repository is an example of how to create an MCP server for managing Kubernetes resources.

Overview

A Model Context Protocol server for interacting with Kubernetes clusters. It provides tools for creating, reading, updating, and deleting Kubernetes resources, as well as observability features like log retrieval and resource inspection.

Components

Tools

The server implements the following tools:

Resource Management

• get_resources: Retrieve Kubernetes resources

  • Takes resource_type (pod, deployment, service, job), namespace (default: "default"), and optional name
  • Returns JSON-formatted resource information

• create_resource: Create new Kubernetes resources

  • Takes resource_type, namespace, and manifest (JSON string)
  • Creates the specified resource in the cluster

• delete_resource: Remove Kubernetes resources

  • Takes resource_type, name, and namespace (default: "default")
  • Deletes the specified resource

Observability

• get_pod_logs: Retrieve container logs

  • Takes pod_name, namespace (default: "default"), optional container, and tail_lines (default: 100)
  • Returns pod logs

• describe_resource: Get detailed resource information

  • Takes resource_type, name, and namespace (default: "default")
  • Returns detailed JSON description of the resource

• get_namespaces: List all namespaces

  • Returns JSON array of namespace information

Advanced Features

• apply_manifest_from_url: Apply Kubernetes manifests from URLs
  • Takes url and optional namespace (default: "default")
  • Downloads and applies the manifest file

Configuration

The server automatically configures Kubernetes client using:

1. In-cluster configuration (when running inside Kubernetes)
2. Local kubeconfig file (when running locally)

Quickstart

Claude Desktop

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

{
  "kubernetes": {
    "command": "uvx",
    "args": [
      "mcp-server-k8s"
    ]
  }
}

Development

Building and Publishing

To prepare the package for distribution:

1. Sync dependencies and update lockfile:

uv sync

2. Build package distributions:

uv build

This will create source and wheel distributions in the dist/ directory.

3. Publish to PyPI:

uv publish

Note: You'll need to set PyPI credentials via environment variables or command flags:

• Token: --token or UV_PUBLISH_TOKEN
• Or username/password: --username/UV_PUBLISH_USERNAME and --password/UV_PUBLISH_PASSWORD

Debugging

Since MCP servers run over stdio, debugging can be challenging. For the best debugging experience, we strongly recommend using the MCP Inspector.

You can launch the MCP Inspector via npm with this command:

npx @modelcontextprotocol/inspector uv --directory $(PWD) run mcp-server-k8s

Upon launching, the Inspector will display a URL that you can access in your browser to begin debugging.