About Mcp K8s Eye
mcp-k8s-eye is an MCP server for managing Kubernetes clusters and analyzing workload status. It is aimed at operators who need to inspect, change and diagnose clusters and applications. It provides resource operation, diagnostic and usage monitoring tools.
Key features
- 01Generic create, read, update and delete for Kubernetes resources
- 02Pod logs, command execution and Deployment scaling
- 03Diagnostics for Pods, Services, Ingress and other resources
- 04CPU and memory usage monitoring for workloads
Use cases
- 01Investigating why Pods or Deployments are not running correctly
- 02Checking Service selectors and Ingress configuration
- 03Reviewing resource usage of workloads in a namespace
MCP support
This project is an MCP server that exposes resource management, diagnostic and monitoring tools to MCP clients. It supports both Stdio and SSE transport modes.
Configuration
Remote servers need no local install. Pick your client, then copy the config or install in one click.
http://localhost:8080/sseclaude mcp add --transport http k8s-eye http://localhost:8080/sse{"mcpServers":{"k8s-eye":{"type":"http","url":"http://localhost:8080/sse"}}}Open in Cursor{"servers":{"k8s-eye":{"type":"http","url":"http://localhost:8080/sse"}}}Open in VS Code{"mcpServers":{"k8s-eye":{"type":"http","url":"http://localhost:8080/sse"}}}{"mcpServers":{"k8s-eye":{"serverUrl":"http://localhost:8080/sse"}}}Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.
Tools
Details
From the project READMEmcp-k8s-eye
mcp-k8s-eye is a tool that can manage kubernetes cluster and analyze workload status.
Features
Core Kubernetes Operations
- Connect to a Kubernetes cluster
- Generic Kubernetes Resources management capabilities
- Support all navtie resources: Pod, Deployment, Service, StatefulSet, Ingress...
- Support CustomResourceDefinition resources
- Operations include: list, get, create, update, delete
- Pod management capabilities (exec, logs)
- Deployment management capabilities (scale)
- Describe Kubernetes resources
- Explain Kubernetes resources
Diagnostics
- Pod diagnostics (analyze pod status, container status, pod resource utilization)
- Service diagnostics (analyze service selector configuration, not ready endpoints, events)
- Deployment diagnostics (analyze available replicas)
- StatefulSet diagnostics (analyze statefulset service if exists, pvc if exists, available replicas)
- CronJob diagnostics (analyze cronjob schedule, starting deadline, last schedule time)
- Ingress diagnostics (analyze ingress class configuration, related services, tls secrets)
- NetworkPolicy diagnostics (analyze networkpolicy configuration, affected pods)
- ValidatingWebhook diagnostics (analyze webhook configuration, referenced services and pods)
- MutatingWebhook diagnostics (analyze webhook configuration, referenced services and pods)
- Node diagnostics (analyze node conditions)
- Cluster diagnostics and troubleshooting
Monitoring
- Pod, Deployment, ReplicaSet, StatefulSet, DaemonSet workload resource usage (cpu, memory)
- Node capacity, utilization (cpu, memory)
- Cluster capacity, utilization (cpu, memory)
Advanced Features
- Multiple transport protocols support (Stdio, SSE)
- Support multiple AI Clients
Tools Usage
Resource Operation Tools
resource_get: Get detailed resource information about a specific resource in a namespaceresource_list: List detailed resource information about all resources in a namespaceresource_create_or_update: Create or update a resource in a namespaceresource_delete: Delete a resource in a namespaceresource_describe: Describe a resource detailed information in a namespacedeployment_scale: Scale a deployment in a namespacepod_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 namespacedeployment_analyze: Diagnose all deployments in a namespacestatefulset_analyze: Diagnose all statefulsets in a namespaceservice_analyze: Diagnose all services in a namespacecronjob_analyze: Diagnose all cronjobs in a namespaceingress_analyze: Diagnose all ingresses in a namespacenetworkpolicy_analyze: Diagnose all networkpolicies in a namespacevalidatingwebhook_analyze: Diagnose all validatingwebhooksmutatingwebhook_analyze: Diagnose all mutatingwebhooksnode_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
- start your mcp sse server
- config your mcp server
{
"mcpServers": {
"k8s eye": {
"url": "http://localhost:8080/sse",
"env": {}
}
}
}
cursor tools

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