Mcp K8s Eye
About
MCP Server for kubernetes management and diagnose your cluster and applications
Details
- Author
- wenhuwang
- GitHub stars
- 28
- Downloads
- 196
- Categories
- Cloud Service
Jump to
- Manage all native Kubernetes resources and CustomResourceDefinitions
- Perform create, read, update, delete, and describe operations
- Execute commands in pods and retrieve pod logs
- Scale deployments
- Diagnose pods, deployments, statefulsets, services, cronjobs, ingresses, network policies, webhooks, and nodes
- Monitor workload resource usage (CPU, memory) for pods, deployments, replicasets, statefulsets, and daemonsets
- Support both Stdio and SSE transport protocols
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
Mcp K8s EyeCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
Clone the repository, build the binary with Go 1.23 or higher, and configure it as an MCP server in either Stdio mode (pointing to the binary and setting HOME for kubeconfig) or SSE mode (starting the SSE server and providing the URL). Use the provided tools such as resource_get, deployment_scale, pod_exec, pod_analyze, and workload_resource_usage via your AI client.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"mcp k8s eye": {
"k8s eye": {
"url": "http://localhost:8080/sse",
"env": []
}
}
}
}
McpServers
{
"k8s eye": {
"url": "http://localhost:8080/sse",
"env": []
}
}
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 resourcesDiagnostics
- [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 troubleshootingMonitoring
- [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 ClientsTools 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": {}
}
}
}
cursor tools

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