Mcp K8s Eye

by wenhuwang

28 196 downloads Not rated yet Apache-2.0

GitHub

Cloud Service

About

MCP Server for kubernetes management and diagnose your cluster and applications

Details

License: Apache-2.0

Explore

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

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 Eye

Command (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

Setting up with Cursor

Open Cursor's settings
Navigate to the MCP section
Click "Add new Global MCP server"
Copy and paste the configuration below based on your operating system

JSON

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

JSON

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

JSON

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

Setting up with Claude Desktop

Open Claude Desktop's settings
Go to the Integrations tab
Click "Add MCP Server"
Use the configuration below based on your operating system

Note: Make sure Claude Desktop is running before attempting to connect.

JSON

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

JSON

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

JSON

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

Setting up with Windsurf

Open Windsurf's preferences
Go to the Integrations section
Click "Add MCP Integration"
Use the configuration below based on your operating system

JSON

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

JSON

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

JSON

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

Setting up with Cline

Open Cline's settings
Navigate to the Integrations section
Click "Add MCP Server"
Copy and paste the configuration below based on your operating system

Note: Make sure to restart Cline after adding the configuration.

JSON

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

JSON

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

JSON

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

Setting up with Goose

Open Goose's preferences
Go to the Integrations tab
Select "MCP Servers"
Click "Add New Server"
Use the configuration below based on your operating system

JSON

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

JSON

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

JSON

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

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.

`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

`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

`workload_resource_usage`

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

- 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

- 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

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

cursor tools

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 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": {}
    }
  }
}

cursor tools

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About

Details

Explore

Setting up with Highlight

From the repository

resource_get

resource_list

resource_create_or_update

resource_delete

resource_describe

deployment_scale

pod_exec

pod_logs

pod_analyze

deployment_analyze

statefulset_analyze

service_analyze

cronjob_analyze

ingress_analyze

networkpolicy_analyze

validatingwebhook_analyze

mutatingwebhook_analyze

node_analyze

workload_resource_usage

Claude Desktop / Cursor

McpServers

Features

Core Kubernetes Operations

Diagnostics

Monitoring

Advanced Features

Tools Usage

Resource Operation Tools

Diagnostics Tools

Monitoring Tools

Requirements

Installation

build the binary

Usage

Stdio mode

SSE mode

cursor tools

Videos about Mcp K8s Eye

Top AI Agents for Cloud Platform Integration (2025) | MCP-Servers

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container-use

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`resource_get`

`resource_list`

`resource_create_or_update`

`resource_delete`

`resource_describe`

`deployment_scale`

`pod_exec`

`pod_logs`

`pod_analyze`

`deployment_analyze`

`statefulset_analyze`

`service_analyze`

`cronjob_analyze`

`ingress_analyze`

`networkpolicy_analyze`

`validatingwebhook_analyze`

`mutatingwebhook_analyze`

`node_analyze`

`workload_resource_usage`