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Kubernetes MCP Server

A powerful MCP (Model Context Protocol) server for Kubernetes operations that allows you to manage your Kubernetes clusters using natural language through AI assistants.

🌟 Features

  • � Resource Listing

    • List pods, services, deployments, and namespaces

    • Get detailed resource information

  • 🔍 Monitoring & Debugging

    • View pod logs with customizable line counts

    • Describe pod details for troubleshooting

    • Get cluster events for debugging

  • ⚡ Operations

    • Port-forward services to local ports

    • Scale deployments up or down

    • Execute kubectl commands through natural language

  • 🎯 Developer Focused

    • Designed for common Kubernetes developer workflows

    • Easy to extend with additional tools

    • Comprehensive error handling

� Available Tools

Tool

Description

Parameters

list-pods

List pods in a namespace

namespace

(optional)

list-services

List services in a namespace

namespace

(optional)

list-deployments

List deployments in a namespace

namespace

(optional)

list-namespaces

List all namespaces

None

describe-pod

Get detailed pod information

pod

(required),

namespace

(optional)

get-logs

Get pod logs

pod

(required),

namespace

(optional),

lines

(optional),

follow

(optional)

port-forward

Port forward a service

service

,

localPort

,

targetPort

(required),

namespace

(optional)

scale-deployment

Scale a deployment

deployment

,

replicas

(required),

namespace

(optional)

get-events

Get cluster events

namespace

(optional)

📋 Requirements

  • Node.js v18+

  • kubectl installed and configured to access your cluster

  • @modelcontextprotocol/cli (optional, for testing)

# Verify kubectl works kubectl get pods # Install MCP CLI (optional) npm install -g @modelcontextprotocol/cli

🔧 Installation

# Clone or download this repository cd kube-mcp # Install dependencies npm install # Run tests to verify setup node test.js

🏃 Running the Server

# Start the MCP server npm start # Or run directly node server.js

The server runs on stdio transport and will output: Kubernetes MCP server running on stdio

🔌 Connecting to MCP Clients

Claude Desktop

Add to your claude_desktop_config.json:

{ "mcpServers": { "kubernetes": { "command": "node", "args": ["/absolute/path/to/kube-mcp/server.js"] } } }

Other MCP Clients

For clients that support MCP, configure them to connect to this server using:

  • Command: node

  • Args: ["/path/to/server.js"]

  • Transport: stdio

💡 Example Usage

Once connected to an MCP-compatible client, you can use natural language like:

  • "List all pods in the default namespace"

  • "Show me the logs for the nginx pod"

  • "Port forward the web service on port 8080 to my local port 3000"

  • "Scale the api deployment to 3 replicas"

  • "What events happened recently in the kube-system namespace?"

🧪 Testing

Run the test script to verify everything is working:

node test.js

This will check:

  • ✅ kubectl availability

  • ✅ Server syntax validation

  • ✅ Server startup capability

  • ✅ Cluster connectivity

🛠️ Development

To add new tools:

  1. Add the tool definition to the tools array in server.js

  2. Add a corresponding case in the CallToolRequestSchema handler

  3. Implement the kubectl command and response formatting

  4. Test with node test.js

⚠️ Security Notes

  • This server executes kubectl commands on your system

  • Ensure your kubectl context is set to the correct cluster

  • Be cautious when scaling deployments or port-forwarding in production

  • Review all operations before execution

📜 License

MIT License - feel free to modify and distribute

🤝 Contributing

Contributions are welcome! Please feel free to submit issues and enhancement requests.

Restart your MCP-enabled client (Cursor AI, Claude Desktop, VS Code MCP extension, etc.)

Now you can issue natural commands like:

  • “Show me all pods in namespace payments”

  • “Port forward postgres service to local 5432”

  • “Get logs from api-pod”

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/thekaranpargaie/kube-mcp'

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