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MCP Kubernetes Server
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MCP Kubernetes Server

mcp - kubernetes - server is an MCP protocol server that serves as a bridge between AI assistants and Kubernetes clusters, enabling Kubernetes operations through natural language interaction.
Developer toolsCloud platform#Kubernetes#AI assistant#Cluster management#Natural language.Python
2.5 points
9.3K
Open Site

Overview

Installation

Content Details

Alternatives

What is MCP Kubernetes Server?

MCP Kubernetes Server is a protocol server that allows AI assistants (such as Claude, Cursor, etc.) to interact with Kubernetes clusters through natural language. It converts users' natural language requests into Kubernetes operations and returns the results in a format that AI tools can understand.

How to use MCP Kubernetes Server?

Simply configure the server information in the supported AI clients, and then you can query or manage Kubernetes clusters using natural language. It supports two installation methods: Docker and UVX.

Applicable scenarios

Suitable for users who need to quickly query the status of Kubernetes clusters, diagnose problems, or perform simple management operations through natural language, especially developers and运维人员 who are not Kubernetes experts but need to interact with the clusters.

Main features

Query Kubernetes resources
Supports querying the status of various resources in the cluster, such as pods, services, deployments, etc.
Execute kubectl and helm commands
Can directly execute kubectl and helm commands and return the results.
Diagnose cluster issues
Get pod logs, events, and status information to help diagnose problems.
Cluster management
Supports basic cluster management operations, such as scaling, rolling updates, etc.
Advantages
No need to memorize complex kubectl commands. You can operate Kubernetes using natural language.
Integrates with multiple AI tools, such as Claude, Cursor, etc.
Provides rich query and management functions, covering most daily Kubernetes operations.
Supports multiple installation methods, including Docker and UVX.
Limitations
Complex operations may still require direct use of kubectl.
Requires pre - configuration of the kubeconfig file.
Some advanced functions may require additional permissions.

How to use

Installation preparation
Ensure that Docker or uv is installed and the kubeconfig file is ready.
Install via Docker
Run the server using Docker and mount the kubeconfig file.
Install via UVX
Run the server through uvx and set the KUBECONFIG environment variable.
AI client configuration
Configure the MCP server information in AI clients (such as Claude, Cursor).

Usage examples

Check cluster status
Quickly understand the overall health status of the cluster
Diagnose pod issues
Find out the reason why the pod cannot run normally
Scale the application
Adjust the number of application replicas

Frequently Asked Questions

What permissions do I need to use this server?
Which AI clients are supported?
How to limit the operation permissions of the server?

Related resources

GitHub repository
Project source code and latest documentation
Kubernetes official documentation
Kubernetes official documentation and tutorials
MCP protocol
Model Context Protocol specification

Installation

Copy the following command to your Client for configuration
{
  "mcpServers": {
    "kubernetes": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "--mount", "type=bind,src=/home/username/.kube/config,dst=/home/mcp/.kube/config",
        "ghcr.io/feiskyer/mcp-kubernetes-server"
      ]
    }
  }
}

{
  "mcpServers": {
    "kubernetes": {
      "command": "uvx",
      "args": [
        "mcp-kubernetes-server"
      ],
      "env": {
        "KUBECONFIG": "<your-kubeconfig-path>"
      }
    }
  }
}
Note: Your key is sensitive information, do not share it with anyone.

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