Kube-MCP

Kube-MCP is a production-grade Model Context Protocol (MCP) server that exposes Kubernetes clusters as structured, AI-callable tools. It enables LLM agents to introspect, diagnose, and remediate cluster issues through natural language—eliminating the need for kubectl expertise.

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Table of Contents

• Architecture
• Features
• Prerequisites
• Installation
• Configuration
• Usage Examples
• Project Structure
• Development
• Roadmap
• Contributing
• License

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Architecture

┌─────────────────────────┐        ┌─────────────────────────┐        ┌─────────────────────────┐
│       LLM Client        │        │      Kube-MCP Server    │        │  Kubernetes API Server  │
│ (Claude, Cursor, Cline) │◀──────▶│     (stdio transport)   │◀──────▶│                         │
└─────────────────────────┘  MCP   └─────────────────────────┘  REST  └─────────────────────────┘

Kube-MCP translates MCP JSON-RPC tool calls into strongly-typed Kubernetes Client-Go API requests. Responses are intentionally optimized into lightweight JSON summaries, preserving LLM context windows while delivering actionable cluster data.

Key Design Principles

• Token-Efficient: Trimmed responses prevent context window exhaustion
• Read-Only by Default: Safe introspection without accidental mutations
• Auto-Detecting Environment: Seamlessly works in-cluster or with local kubeconfig
• Graceful Degradation: Continues operating even when metrics-server is unavailable

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Features

Available MCP Tools

Category	Tool	Parameters	Description
Pods	list_pods	namespace	List pods with status, restarts, ready count, node, and age
	get_pod	name, namespace	Fetch detailed pod specification and status
	get_logs	pod, namespace, container, tail, previous	Stream container logs with 50KB cap and crashloop diagnostics
Nodes	list_nodes	—	List nodes with readiness, roles, version, and OS
	describe_node	name	Fetch node capacity, allocatable, taints, and conditions
Workloads	list_deployments	namespace	List deployments with replica counts and availability
	get_deployment	name, namespace	Fetch full deployment specification
	check_rollout_status	deployment, namespace	Monitor deployment rollout progress
Networking	list_services	namespace	List services with type, ClusterIP, and ports
	list_ingresses	namespace	List ingresses with hosts and load balancer addresses
Storage	get_pvc_status	namespace	List PVCs with binding status, capacity, and storage class
Config	list_configmaps	namespace	List ConfigMaps with names and keys (values omitted for safety)
Namespaces	list_namespaces	—	List namespaces with status phase and age
Events	get_events	namespace, reason	Fetch namespace events with optional reason filtering
Metrics	get_resource_usage	pod_name, namespace, node_name	Query CPU/memory usage (pod, node, or cluster-wide)

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Prerequisites

Requirement	Version	Notes
Go	1.26+	Download
Kubernetes	1.24+	Valid kubeconfig or in-cluster ServiceAccount
metrics-server	Optional	Required for get_resource_usage tool

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Installation

Build from Source

git clone https://github.com/Aamod007/Kube-MCP.git
cd Kube-MCP
go build -o kubemcp ./cmd/server

Install Binary

sudo install kubemcp /usr/local/bin/kubemcp

Verify Installation

kubemcp --help

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Configuration

Kube-MCP uses the standard MCP stdio transport, making it compatible with any MCP-compliant client.

Environment Variables

Variable	Required	Default	Description
KUBECONFIG	No	~/.kube/config	Path to Kubernetes config file

Client Configuration

Claude Desktop

Edit ~/Library/Application Support/Claude/claude_desktop_config.json:

{
  "mcpServers": {
    "kubemcp": {
      "command": "/usr/local/bin/kubemcp",
      "env": {
        "KUBECONFIG": "/Users/yourname/.kube/config"
      }
    }
  }
}

Cursor

1. Navigate to Settings > Features > MCP
2. Click Add New MCP Server
3. Configure:
   • Name: KubeMCP
   • Type: command
   • Command: /usr/local/bin/kubemcp

Cline

Edit cline_mcp_settings.json:

{
  "mcpServers": {
    "kubemcp": {
      "command": "/usr/local/bin/kubemcp",
      "env": {
        "KUBECONFIG": "/Users/yourname/.kube/config"
      }
    }
  }
}

Supported Platforms

• Claude Desktop / Claude Code
• Cursor
• VS Code + GitHub Copilot
• Cline
• OpenCode / OpenClaw / Codex
• Gemini CLI / Antigravity / Pi Agent

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Usage Examples

Once configured, interact with your cluster using natural language:

List all pods in the production namespace

Why is the nginx deployment failing? Check the logs and events.

Show me the top 5 pods by memory usage across the cluster

Find all Failed events in kube-system from the last hour

Describe the node worker-01 and check its resource pressure conditions

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Project Structure

Kube-MCP/
├── cmd/
│   └── server/
│       └── main.go              # Application entrypoint
├── internal/
│   ├── k8s/
│   │   ├── client.go            # Kubernetes client initialization
│   │   └── metrics.go           # Metrics-server API wrapper
│   └── tools/
│       ├── registry.go          # Tool registration dispatcher
│       ├── helpers.go           # Shared response utilities
│       ├── pods.go              # Pod management tools
│       ├── nodes.go             # Node management tools
│       ├── deployments.go       # Deployment & rollout tools
│       ├── services.go          # Service & ingress tools
│       ├── events.go            # Event querying tools
│       ├── config.go            # ConfigMap tools
│       ├── storage.go           # PVC status tools
│       ├── namespaces.go        # Namespace listing tools
│       └── resource.go          # CPU/memory usage tools
├── go.mod
├── go.sum
└── README.md

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Development

Code Quality

go fmt ./...
go vet ./...
go build ./...

Run Locally

go run ./cmd/server

Testing

go test ./... -v

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Roadmap

Milestone	Features	Status
M0/M1	Read-only tools, stdio transport	Completed
M2	Write tools (apply, delete, patch) with read/write mode toggles	Planned
M3	HTTP SSE transport for remote deployments	Planned
M4	Agentic diagnostic loop (autonomous troubleshooting)	Planned
M5	Docker container publishing	Planned
M6	Helm charts for in-cluster deployment	Planned

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Contributing

Contributions are welcome! Please follow these steps:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'feat: add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

Guidelines

• Follow conventional commit messages
• Add tests for new functionality
• Update documentation for user-facing changes
• Ensure go fmt and go vet pass before submitting

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Security

• Read-Only by Default: All tools are introspection-only
• No Secret Exposure: ConfigMap values are intentionally omitted
• Log Caps: Log output is limited to 50KB to prevent token exhaustion
• RBAC Respected: Operations are scoped to the configured ServiceAccount permissions

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License

This project is licensed under the MIT License. See LICENSE for details.

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Acknowledgments

• Model Context Protocol by Anthropic
• Kubernetes Client-Go
• mcp-go