Kubeview MCP

🚀 KubeView MCP – Kubernetes Model Context Protocol Server

KubeView MCP is a read - only Model Context Protocol (MCP) server. It allows AI agents (such as Cursor IDE, Claude Code CLI, Codex CLI, Gemini CLI, etc.) to safely inspect, diagnose, and debug Kubernetes clusters. It offers a comprehensive set of tools for Kubernetes, Helm, Argo Workflows, and Argo CD. For more details about the benefits of code mode and its implementation, refer to Evicting MCP tool calls from your Kubernetes cluster.

🚀 Quick Start

Prerequisites

• Node.js ≥ 18
• Access to a Kubernetes cluster
• Optionally, CLIs installed in current $PATH: helm, argo, argocd

Installation

# start the server
npx -y kubeview-mcp

# install as a claude code mcp server
claude mcp add kubernetes -- npx kubeview-mcp

Configuration for MCP Clients

Add the following to your mcpServers configuration (e.g., in Cursor or Claude Desktop):

{
  "mcpServers": {
    "kubeview": {
      "command": "npx",
      "args": ["-y", "kubeview-mcp"]
    }
  }
}

Environment Variables

Configure the server using the following environment variables:

✨ Features

• 🧠 Code Mode: A sandboxed TypeScript environment for complex reasoning and multi - step workflows.
• 🛡️ Read - Only & Safe: Designed for production safety with zero write access and sensitive data masking.
• ☸️ Kubernetes Integration: List/get resources, fetch metrics, stream logs and events, execute commands, and use tools to diagnose network issues.
• 📦 Helm Support: Inspect releases, values, manifests, and history.
• 🐙 Argo Ecosystem: Manage Argo Workflows and Argo CD applications using the direct Kubernetes API or CLI.

🛠️ Tools Overview

Kubernetes

• kube_list: List resources or get cluster diagnostics.
• kube_get: Describe specific resources (supports all K8s types).
• kube_metrics: Fetch CPU/memory metrics for nodes and pods.
• kube_logs: Fetch or stream container logs.
• kube_exec: Execute commands in containers (read - only recommended).
• kube_port: Port - forward to pods/services.
• kube_net: Run in - cluster network diagnostics.

Helm

• helm_list: List Helm releases.
• helm_get: Fetch release values, manifests, and history.

Argo

• argo_list / argo_get: Manage Argo Workflows.
• argocd_app: Inspect Argo CD applications and resources.

Utilities

• run_code: Execute sandboxed TypeScript code for complex tasks.

🧠 Code Mode

Inspired by Code execution with MCP, KubeView comes with a code - mode runtime. It allows agents to explore the API, search tools, and execute complex workflows in a sandboxed environment.

What it provides

• MCP Bridge Layer: Seamlessly connects to all registered MCP server tools.
• Dynamic TypeScript Definitions: Automatically converts tool schemas into a strongly - typed global.d.ts resource, enabling agents to use valid TypeScript patterns and enjoy type safety without hallucinating parameters.
• Tool Search Utilities: Runtime helpers like tools.search() and tools.list() allow agents to progressively discover capabilities without needing to load the entire schema context upfront.
• Sandboxed Execution: A locked - down Node.js environment (via vm) with controlled access to the console and the tools global object, ensuring safe execution of agent - generated code.

Usage

For complex tasks requiring logic, loops, or data processing, use Code Mode:

"env": { "MCP_MODE": "code" }

💡 Pro Tip: Code Mode Prompt

The server includes a built - in prompt named code - mode that injects the full TypeScript API documentation, tool overview, and examples into the context.

In Cursor IDE: Simply type /kubeview/code - mode in the prompt (or select it from the / prompt menu). This gives the AI the exact context it needs to write correct run_code scripts immediately.

💻 Local Development

1. Clone & Install:

   git clone https://github.com/mikhae1/kubeview-mcp.git
   cd kubeview-mcp
   npm install
   

2. Build & Run:

   npm run build
   npm start
   

3. Test:

   npm test
   

CLI Usage

You can test tools directly via the CLI:

npm run command -- kube_list --namespace=default

📄 License

MIT © mikhae1