MCP server · Developer tools

Kubernetes MCP server

Lets your AI look at and manage your Kubernetes cluster, like checking pods, logs and deployments for you.

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This is a small helper that connects your AI assistant to a Kubernetes cluster. Kubernetes is the system many companies use to run their apps in the cloud, and this helper lets your AI ask it questions and make changes. It is handy if you work with a Kubernetes cluster and want to check on things without typing every command yourself.

What is an MCP server? The 30-second version

On its own, your AI can only chat. An MCP server is a small helper program that gives your AI a new skill or a connection to another tool. This one connects your AI to your Kubernetes cluster, so when you ask about your pods or deployments, the AI can actually go and look. You stay in the chat, and the helper does the running around.

What this MCP server does

You ask your AI something like which pods are running in a namespace. The AI uses this helper, which runs the usual kubectl commands against your cluster. The cluster sends back the answer, and the helper hands it to your AI. Your AI then explains it to you in plain words, right in the chat. If you ask it to change something, like scaling a deployment, it can do that too.

Flow diagram: you ask your AI “Which pods are running in my cluster?”, the Kubernetes MCP server connects it to Your Kubernetes cluster, and you get back plain answer in chat.

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What you can do with it

List pods, deployments, services and other resources in your cluster
Show logs from a pod so you can see what went wrong
Describe a resource to get its full details and events
Apply a YAML file to create or update resources
Scale a deployment up or down
Install or upgrade a Helm chart
Run a troubleshooting flow to diagnose a misbehaving pod

Try asking your AI

“List all pods in the default namespace”
“Show me the logs from the checkout pod”
“Why is the payments deployment not starting?”
“Scale the web deployment to 3 replicas”

What it gives back to you

You get answers in the chat: lists of pods or services, log lines, descriptions of a resource, or a short summary of what your AI found. If you asked for a change, it tells you what it did, like scaling a deployment to 3 replicas. It can also walk you through a diagnosis step by step when something is broken.

Before you start

What you need

kubectl installed on your computer and working in your terminal
A kubeconfig file that can reach your cluster (usually at ~/.kube/config)
Access to a Kubernetes cluster, like minikube, Rancher Desktop or GKE
Helm v3 installed if you want to use Helm features (optional)

Good to know

It can change or delete things in your cluster, so be careful with delete and cleanup commands, and consider the non-destructive mode if you only want to look.

Install it with your AI

Add Kubernetes MCP server to your AI, no technical skills needed

You don't install anything by hand. You copy one prompt, paste it into an AI that can work on your computer, and it checks, installs and connects the server for you, asking you when it needs something.

Sign in to get the install prompt

Members get a ready-made prompt that lets the Claude desktop app check Kubernetes MCP server, install it and connect it for them, step by step. You don't need any technical skills: you copy, paste and answer a few questions. Your connected AI can also find and install any of the 4,066 MCP servers here for you.