What is k8s_pilot?

k8s_pilot is a lightweight, centralized control plane server for managing multiple Kubernetes clusters at once. It provides a single interface to observe and control all your clusters.

What are the prerequisites for using k8s_pilot?

You need Python 3.13 or higher, the uv package manager, and access to your Kubernetes clusters (either through ~/.kube/config or in-cluster configuration).

How do I install k8s_pilot?

Clone the repository from GitHub, navigate to the cloned directory, and run uv run --with mcp[cli] mcp run k8s_pilot.py.

How can I use k8s_pilot with Claude Desktop?

Add a configuration to Claude’s settings that specifies the command and arguments to run the k8s_pilot MCP server. Ensure the path to the cloned repository is correctly specified in the configuration.

What is MCP and how does k8s_pilot use it?

MCP (Model Context Protocol) is an open protocol that standardizes how applications provide context to LLMs. k8s_pilot is powered by MCP, allowing it to interact with AI models like Claude and provide context-aware operations.

What Kubernetes resources can I manage with k8s_pilot?

You can manage Deployments, Services, Pods, ConfigMaps, Secrets, Ingresses, StatefulSets, DaemonSets, Roles, ClusterRoles, PersistentVolumes, and Claims.

Can I create and delete namespaces with k8s_pilot?

Yes, you can create and delete namespaces, list all resources in a namespace, and manage labels and resource quotas.

What node management features does k8s_pilot offer?

You can view node details, cordon/uncordon nodes, label/taint nodes, and list pods per node.

Where can I find the license information for k8s_pilot?

The project is licensed under the MIT License. You can find the details in the LICENSE file in the repository.

How does k8s_pilot integrate with UBOS?

k8s_pilot integrates with UBOS by providing a streamlined way to manage the Kubernetes infrastructure used for deploying and scaling AI Agents. UBOS can leverage k8s_pilot’s API to automate deployments, monitor agent health, and manage resources efficiently.