mcp-k8s-eye

Kubernetes management and diagnostics tool with MCP protocol support.

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mcp-k8s-eye enables users to manage and analyze Kubernetes clusters using standardized Model Context Protocol (MCP) interfaces. It offers comprehensive resource operations, diagnostics, and resource usage monitoring through both stdio and SSE transports. Supporting generic and custom resource management along with advanced diagnostic tooling, it is geared for integration with AI clients and other MCP consumers.

Key Features

Standardized MCP protocol support (stdio, SSE)

Management of generic and custom Kubernetes resources

Pod and deployment operations (exec, logs, scaling)

Detailed resource listing, creation, updating, and deletion

Comprehensive diagnostics for pods, services, deployments, nodes, and more

Workload resource usage monitoring (CPU, memory)

Multiple AI client support

Advanced analysis of networking and webhook configurations

Cluster-wide resource and utilization diagnostics

Customizable integration via environment and protocol configuration

Use Cases

Automated Kubernetes cluster management for platform teams

Operational diagnostics for troubleshooting Kubernetes workloads

Monitoring resource utilization at granular and cluster-wide levels

Integration into AI-powered DevOps assistants or chat agents

Custom resource definition (CRD) operations in managed environments

Real-time cluster health and status analysis

Infrastructure as Code (IaC) workflows for resource deployment and updates

Network policy and webhook configuration audits

Analysis of cluster resource constraints and bottlenecks

Cluster administration through standardized context protocols

README

mcp-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 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

start your mcp sse server
config your mcp server

{
  "mcpServers": {
    "k8s eye": {
      "url": "http://localhost:8080/sse",
      "env": {}
    }
  }
}

cursor tools

Star History

Repository Owner

wenhuwang

User

Repository Details

Language Go

Default Branch main

Size 389 KB

Contributors 1

License Apache License 2.0

MCP Verified Nov 11, 2025

Programming Languages

100%

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mcp-k8s-eye

Key Features

Use Cases

README

mcp-k8s-eye

Features

Core Kubernetes Operations

Diagnostics

Monitoring

Advanced Features

Tools Usage

Resource Operation Tools

Diagnostics Tools

Monitoring Tools

Requirements

Installation

Usage

Stdio mode

SSE mode

cursor tools

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Repository Details

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