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Works with

Claude CodeClaude DesktopCursorVS CodeClineCodex CLIOpenClaw+ any MCP client

Install to Claude Code

This server doesn't publish a one-line install command. Follow the setup in the source repository.

Summary

MCP Server for kubernetes management, and analyze your cluster, application health

README.md

mcp-k8s-eye

mcp-k8s-eye is a tool that can manage kubernetes cluster and analyze workload status.

Features

Core Kubernetes Operations

  • [x] Connect to a Kubernetes cluster
  • [x] Generic Kubernetes Resources management capabilities
  • Support all navtie resources: Pod, Deployment, Service, StatefulSet, Ingress...
  • Support CustomResourceDefinition resources
  • Operations include: list, get, create, update, delete
  • [x] Pod management capabilities (exec, logs)
  • [x] Deployment management capabilities (scale)
  • [x] Describe Kubernetes resources
  • [ ] Explain Kubernetes resources

Diagnostics

  • [x] Pod diagnostics (analyze pod status, container status, pod resource utilization)
  • [x] Service diagnostics (analyze service selector configuration, not ready endpoints, events)
  • [x] Deployment diagnostics (analyze available replicas)
  • [x] StatefulSet diagnostics (analyze statefulset service if exists, pvc if exists, available replicas)
  • [x] CronJob diagnostics (analyze cronjob schedule, starting deadline, last schedule time)
  • [x] Ingress diagnostics (analyze ingress class configuration, related services, tls secrets)
  • [x] NetworkPolicy diagnostics (analyze networkpolicy configuration, affected pods)
  • [x] ValidatingWebhook diagnostics (analyze webhook configuration, referenced services and pods)
  • [x] MutatingWebhook diagnostics (analyze webhook configuration, referenced services and pods)
  • [x] Node diagnostics (analyze node conditions)
  • [ ] Cluster diagnostics and troubleshooting

Monitoring

  • [x] Pod, Deployment, ReplicaSet, StatefulSet, DaemonSet workload resource usage (cpu, memory)
  • [ ] Node capacity, utilization (cpu, memory)
  • [ ] Cluster capacity, utilization (cpu, memory)

Advanced Features

  • [x] Multiple transport protocols support (Stdio, SSE)
  • [x] Support multiple AI Clients

Tools Usage

Resource Operation Tools

  • resource_get: Get detailed resource information about a specific resource in a namespace
  • resource_list: List detailed resource information about all resources in a namespace
  • resource_create_or_update: Create or update a resource in a namespace
  • resource_delete: Delete a resource in a namespace
  • resource_describe: Describe a resource detailed information in a namespace
  • deployment_scale: Scale a deployment in a namespace
  • pod_exec: Execute a command in a pod in a namespace`
  • pod_logs: Get logs from a pod in a namespace

Diagnostics Tools

  • pod_analyze: Diagnose all pods in a namespace
  • deployment_analyze: Diagnose all deployments in a namespace
  • statefulset_analyze: Diagnose all statefulsets in a namespace
  • service_analyze: Diagnose all services in a namespace
  • cronjob_analyze: Diagnose all cronjobs in a namespace
  • ingress_analyze: Diagnose all ingresses in a namespace
  • networkpolicy_analyze: Diagnose all networkpolicies in a namespace
  • validatingwebhook_analyze: Diagnose all validatingwebhooks
  • mutatingwebhook_analyze: Diagnose all mutatingwebhooks
  • node_analyze: Diagnose all nodes in cluster

Monitoring Tools

  • workload_resource_usage: Get pod/deployment/replicaset/statefulset resource usage in a namepace (cpu, memory)

Requirements

  • Go 1.23 or higher
  • kubectl configured

Installation

# clone the repository
git clone https://github.com/wenhuwang/mcp-k8s-eye.git
cd mcp-k8s-eye

# build the binary
go build -o mcp-k8s-eye

Usage

Stdio mode

{
  "mcpServers": {
    "k8s eye": {
      "command": "YOUR mcp-k8s-eye PATH",
      "env": {
        "HOME": "USER HOME DIR"
      },
    }
  }
}

env.HOME is used to set the HOME directory for kubeconfig file.

SSE mode

  1. start your mcp sse server
  2. config your mcp server
{
  "mcpServers": {
    "k8s eye": {
      "url": "http://localhost:8080/sse",
      "env": {}
    }
  }
}

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