Thanhdeptr/K8s_AI_Assistant_MCP
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The Model Context Protocol (MCP) Server is a powerful backend solution designed to facilitate AI-driven Kubernetes management through natural language processing and automated command execution.
🚀 K8s AI Assistant MCP ( NO MORE WORKING)
A comprehensive Kubernetes management solution combining MCP (Model Context Protocol) Server and Rancher UI Extensions for intelligent, AI-powered Kubernetes cluster management.
📋 Table of Contents
- Overview
- Architecture
- Components
- Features
- Demo
- Installation
- Usage
- Development
- License
- Acknowledgments
🎯 Overview
This project integrates two powerful technologies to create a seamless Kubernetes management experience:
- MCP Server for Kubernetes - AI-powered command interface for Kubernetes operations
- Rancher UI Extensions - Visual interface extensions for Rancher management platform
The combination provides both command-line AI assistance and visual management capabilities through a unified interface.
🔄 System Workflow
Architecture Overview
The K8s AI Assistant follows a multi-layered architecture that processes natural language queries through AI analysis and executes Kubernetes operations via MCP protocols.
graph LR
A[User Input] --> B[Rancher UI]
B --> C[Backend API]
C --> D[Ollama AI]
D --> E[MCP Server]
E --> F[Kubernetes]
F --> E
E --> D
D --> C
C --> B
B --> A
style A fill:#e1f5fe
style B fill:#fff3e0
style C fill:#f3e5f5
style D fill:#e8f5e8
style E fill:#fff8e1
style F fill:#fce4ec
Core Components
| Component | Technology | Protocol | Port | Purpose |
|---|---|---|---|---|
| Frontend | Vue.js + Rancher Shell | HTTP/HTTPS | 8005 | User interface and chat experience |
| Backend API | Express.js | HTTP | 8055 | Request routing and response formatting |
| AI Model | Ollama (gpt-oss:20b) | OpenAI-compatible API | 11434 | Natural language processing and intent mapping |
| MCP Server | Node.js + TypeScript | JSON-RPC + SSE | 3000 | Kubernetes command execution |
| Kubernetes | kubectl + Helm | Kubernetes API | 6443 | Cluster management and resource operations |
Request Flow
- User submits natural language query via Rancher UI extension
- Backend API validates and routes request to AI model
- Ollama AI analyzes intent and maps to Kubernetes operations
- MCP Server executes kubectl/Helm commands via JSON-RPC
- Kubernetes API returns cluster data and operation results
- Response chain processes data through AI formatting
- Frontend displays formatted results (tables, logs, insights)
Key Features
- Natural Language Processing: Converts user queries to Kubernetes commands
- Real-time Execution: Live cluster data retrieval and operation execution
- Intelligent Formatting: AI-powered response formatting and insights
- Secure Operations: RBAC-compliant cluster access and audit logging
- Extensible Architecture: Modular design for easy feature additions
🏗️ Architecture
┌─────────────────────────────────────────────────────────────┐
│ K8s AI Assistant MCP │
├─────────────────────────────────────────────────────────────┤
│ ┌─────────────────┐ ┌─────────────────────────────────┐ │
│ │ MCP Server │ │ Rancher UI Extensions │ │
│ │ (Backend) │ │ (Frontend) │ │
│ │ │ │ │ │
│ │ • kubectl ops │ │ • Visual dashboards │ │
│ │ • Helm support │ │ • Resource management UI │ │
│ │ • AI diagnosis │ │ • Real-time monitoring │ │
│ │ • Port forward │ │ • Custom extensions │ │
│ └─────────────────┘ └─────────────────────────────────┘ │
│ │ │ │
│ └───────────┬───────────────┘ │
│ │ │
│ ┌─────────────────────────────────────────────────────────┐ │
│ │ Kubernetes Cluster │ │
│ │ ┌─────────────┐ ┌─────────────┐ ┌─────────────────┐ │ │
│ │ │ Pods │ │ Services │ │ Deployments │ │ │
│ │ └─────────────┘ └─────────────┘ └─────────────────┘ │ │
│ └─────────────────────────────────────────────────────────┘ │
└─────────────────────────────────────────────────────────────┘
🔧 Components
1. MCP Server for Kubernetes (mcp-server-kubernetes/)
Forked from: Flux159/mcp-server-kubernetes
The MCP Server provides AI-powered Kubernetes management through natural language commands and automated operations.
Key Features:
- Unified kubectl API - Complete kubectl command support
- AI-powered diagnostics - Automated troubleshooting with
k8s-diagnose - Helm operations - Chart management and deployment
- Port forwarding - Secure access to cluster services
- Non-destructive mode - Safe read-only operations
- Secrets masking - Security-focused data handling
Available Commands:
# Resource Management
kubectl_get, kubectl_describe, kubectl_create, kubectl_apply
kubectl_delete, kubectl_scale, kubectl_patch, kubectl_rollout
# Monitoring & Debugging
kubectl_logs, port_forward, k8s-diagnose
# Helm Operations
install_helm_chart, upgrade_helm_chart, uninstall_helm_chart
# Context Management
kubectl_context, list_api_resources, explain_resource
2. Rancher UI Extensions (rancher-ui/)
Forked from: rancher/ui-plugin-examples
The Rancher UI Extensions provide visual management interfaces for Kubernetes resources through the Rancher platform.
Key Features:
- Visual dashboards - Real-time cluster monitoring
- Resource management UI - Intuitive resource operations
- Custom extensions - Extensible plugin architecture
- Multi-cluster support - Manage multiple clusters
- Role-based access - Secure access control
Extension Types:
- Clock Extension - Real-time cluster time display
- Homepage Extension - Custom dashboard views
- CRD Extensions - Custom resource definitions
- Node Driver Extensions - Cloud provider integrations
- Top-level Product Extensions - Complete product integrations
✨ Features
AI-Powered Management
- Natural language Kubernetes commands
- Automated troubleshooting and diagnostics
- Intelligent resource recommendations
- Predictive scaling and optimization
Visual Interface
- Real-time cluster monitoring dashboards
- Drag-and-drop resource management
- Visual pod and service topology
- Interactive log viewing
Security & Compliance
- Role-based access control (RBAC)
- Secrets management and masking
- Audit logging and compliance reporting
- Secure port forwarding
Multi-Cluster Support
- Unified management across multiple clusters
- Cross-cluster resource monitoring
- Centralized configuration management
- Cluster health scoring
🎬 Demo
Demo Screenshots
Rancher UI Extension Interface

Rancher UI Extension interface showing Kubernetes management capabilities
Additional Demo Content (Coming Soon)
📸 More Demo Images
Additional screenshots and videos demonstrating the K8s AI Assistant in action
Planned Demo Content:
- MCP Server command-line interface
- AI-powered troubleshooting workflow
- Multi-cluster management interface
- Real-time monitoring and alerts
- Helm chart deployment process
- Port forwarding and service access
- Custom extension development
Interactive Demo
🔗 Live Demo Placeholder
Coming soon: Interactive demo environment for hands-on experience
🚀 Installation
Prerequisites
- Kubernetes cluster (local or remote)
- Node.js 18+ and npm/bun
- kubectl configured with cluster access
- Rancher Manager (for UI extensions)
- Ollama server (for AI model)
Quick Start
- Clone the repository:
git clone https://github.com/Thanhdeptr/K8s_AI_Assistant_MCP.git
cd K8s_AI_Assistant_MCP
- Install MCP Server:
cd mcp-server-kubernetes
npm install
npm run build
- Install Rancher UI Extensions:
cd ../rancher-ui
npm install
- Configure Claude Desktop:
{
"mcpServers": {
"k8s-ai-assistant": {
"command": "node",
"args": ["/path/to/K8s_AI_Assistant_MCP/mcp-server-kubernetes/dist/index.js"]
}
}
}
- Deploy Rancher Extensions:
# Build and package extensions
npm run build
npm run package
# Deploy to Rancher
helm install k8s-ai-extensions ./charts/
Detailed Setup Instructions
For detailed setup instructions including how to run the MCP server and backend server, see .
📖 Usage
MCP Server Commands
# Get all pods in default namespace
kubectl_get pods
# Describe a specific deployment
kubectl_describe deployment my-app
# Scale a deployment
kubectl_scale deployment my-app --replicas=5
# Diagnose pod issues
k8s-diagnose my-app-pod
# Port forward to a service
port_forward service/my-app-service 8080:80
Rancher UI Extensions
- Access Rancher Manager
- Navigate to Extensions
- Install K8s AI Assistant extensions
- Access custom dashboards and tools
🛠️ Development
Project Structure
K8s_AI_Assistant_MCP/
├── mcp-server-kubernetes/ # MCP Server backend
│ ├── src/ # Source code
│ ├── tests/ # Unit tests
│ └── dist/ # Built artifacts
├── rancher-ui/ # Rancher UI extensions
│ ├── pkg/ # Extension packages
│ ├── charts/ # Helm charts
│ └── assets/ # Extension assets
└── docs/ # Documentation
Development Setup
- MCP Server Development:
cd mcp-server-kubernetes
npm run dev # Development mode with hot reload
npm run test # Run tests
npm run build # Build for production
- Rancher UI Development:
cd rancher-ui
npm run dev # Development server
npm run build # Build extensions
npm run package # Package for deployment
Testing
# Run all tests
npm run test:all
# Test MCP Server only
cd mcp-server-kubernetes && npm run test
# Test UI extensions only
cd rancher-ui && npm run test
📄 License
This project is licensed under the MIT License - see the file for details.
🙏 Acknowledgments
This project builds upon the excellent work of the following open-source projects:
MCP Server for Kubernetes
- Original Repository: Flux159/mcp-server-kubernetes
- Author: Paras Patel and Suyog Sonwalkar
- License: MIT License
- Description: MCP Server providing Kubernetes management commands through AI interfaces
Rancher UI Plugin Examples
- Original Repository: rancher/ui-plugin-examples
- Author: Rancher Labs
- License: Apache 2.0
- Description: Example UI extensions for Rancher management platform
Key Contributors
- Flux159 - MCP Server development and maintenance
- Rancher Labs - UI extension framework and examples
- Open Source Community - Continuous improvements and feedback
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