MCP Kubernetes

An experimental Kubernetes MCP server that exposes Kubernetes functionality to AI chat interfaces via kubectl, enabling AI assistants to help analyze and manage cluster resources.

Artificial intelligence chatbots Developer tools #Kubernetes integration #AI assistant #Cluster management #kubectl tool .Rust

rating : 2 points

downloads : 20

update time : 2025-04-29

What is the Kubernetes MCP Server?

This is a bridge service that connects an AI assistant to a Kubernetes cluster. It allows you to communicate with the AI in natural language, and the AI automatically converts it into kubectl commands to query or manage your Kubernetes resources.

How to use the Kubernetes MCP Server?

After installing the service, simply chat with the AI as usual, ask questions about the Kubernetes cluster or request operations to be performed. The AI will interact with the server via the MCP protocol and return the results.

Use cases

Particularly suitable for users who need to quickly query the cluster status, troubleshoot problems, or perform routine management tasks but don't want to memorize complex kubectl commands. Also suitable for team knowledge sharing and new - comer training.

Main features

Full kubectl integrationSupports all kubectl commands, including common operations such as get, describe, logs, etc.

AI assistant interactionCommunicate with the AI in natural language without memorizing complex commands

Resource analysisThe AI can help analyze resource status, identify problems, and provide suggestions

Advantages and limitations

Advantages

Lower the threshold for using Kubernetes, allowing non - technical personnel to query the cluster status

Improve operational efficiency by quickly obtaining the required information through natural language

Built - in knowledge base can explain professional terms and concepts

Highly scalable, more analysis functions can be added in the future

Limitations

Requires proper configuration of RBAC permissions, posing certain security risks

Complex operations may require multiple interactions to be accurately expressed

Relies on the AI's understanding ability, and sometimes the question formulation may need to be adjusted

How to use

Install the service

Clone the repository and build the project

Configure the AI assistant

Configure the AI platform you are using to connect to the MCP server

Start using

Ask questions about the Kubernetes cluster or request operations through the AI chat interface

Usage examples

Query Pod statusQuickly understand the running status of Pods in the cluster

View service logsGet the logs of a specific service to troubleshoot problems

Resource explanationUnderstand unfamiliar Kubernetes resources

Frequently Asked Questions

Is this service secure?

Which AI platforms are supported?

How much technical knowledge is required to use it?

Related resources

Official documentation of the MCP protocol

Understand the technical details of the MCP protocol

Official Kubernetes documentation

Authoritative reference materials for Kubernetes

Example configuration repository

Get the latest code and example configurations

🚀 Kubernetes MCP Server

An experimental Model Context Protocol (MCP) server that exposes Kubernetes capabilities to AI chat interfaces via kubectl. This project demonstrates how to integrate Kubernetes into an AI assistant, enabling it to analyze and manage your cluster resources using familiar kubectl commands.

🚀 Quick Start

The Kubernetes MCP Server is an innovative project that bridges the gap between AI chat interfaces and Kubernetes clusters. It empowers AI assistants to interact with your Kubernetes resources using the well - known kubectl commands.

✨ Features

Resource Discovery: Enable your AI assistant to list and describe resources using kubectl commands.
Troubleshooting: Let the AI assist in analyzing logs and resource states.
Resource Management: Get AI help to create or modify resources.
Documentation: Ask the AI to explain specific resources in the cluster.
Security Analysis: Have the AI identify potential security issues in the configuration.

💻 Usage Examples

Basic Usage

User: Can you show all pods in the default namespace?
AI: Let me check for you...
[Execute the command "get pods -n default" using the kubectl tool]
Here are the pods in the default namespace:
NAME                     READY   STATUS    RESTARTS   AGE
nginx-7c658794b9-2j4k5   1/1     Running   0          2d

📚 Documentation

Future Possibilities

The current implementation lays the foundation for many powerful interactions:

Complex troubleshooting scenarios using multiple kubectl commands.
Automated resource analysis and recommendations.
Interactive debugging sessions.
Security scans and recommendations.
Performance optimization suggestions.

📦 Installation

Clone the repository:

git clone https://github.com/yourusername/mcp-kubernetes.git
cd mcp-kubernetes

Build the project:

cargo build --release

Configure your AI assistant to use the server (specific steps depend on your AI platform).

Requirements

Rust 1.70 or higher.
kubectl installed and configured.
A Kubernetes cluster with appropriate permissions.
kubeconfig configured for your cluster.

Configuration

The server uses the default kubeconfig and kubectl installation. Ensure you have the appropriate permissions to execute the required commands.

🔧 Technical Details

Security Considerations

Since this server allows the execution of arbitrary kubectl commands, the following points need attention:

Run with appropriate RBAC permissions.
Consider implementing command validation or a whitelist.
Monitor and audit command execution.
Use in a controlled environment.

📄 License

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

Acknowledgments

This project is based on the mcpr project (created by @conikeec). Thanks to the author for creating this excellent protocol and implementation.

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