Runpodctl

Runpodctl is a command-line tool designed for managing GPU pods and serverless endpoints on the Runpod platform. It is particularly useful for developers and data scientists who need to deploy and manage AI workloads efficiently.

000Updated 3w ago

Management Tools

Quick InstallView Source

$ npx skills add https://github.com/runpod/skills --skill runpodctl

Overview

About This Skill

Runpodctl is a command-line interface tool that enables developers and data scientists to manage GPU pods, serverless endpoints, templates, volumes, and models on the Runpod platform. The tool provides comprehensive commands for creating, listing, updating, and deleting GPU workloads across Linux, macOS, and Windows. You can deploy containerized applications using custom Docker images or pre-configured templates, search the Runpod Hub marketplace for deployable repositories, and configure scaling policies and resource allocation for serverless endpoints. Runpodctl streamlines GPU resource management, making it easier to provision and monitor AI workloads without navigating the web console.

How to Use

Install using the official installer or Homebrew for macOS.

Use Cases

Deploying models on serverless GPU endpoints

Managing GPU pods and templates

Handling serverless workloads effectively

Integrating with other Runpod CLI tools

Setup & Installation

Quick Install

Terminal

$ npx skills add https://github.com/runpod/skills --skill runpodctl

Alternative Install (Git Clone)

git clone https://github.com/runpod/skills

Requirements

Claude Code or compatible AI agent

Quick Start Guide

Install the Skill

Copy the install command above and run it in your terminal.

Open Your AI Agent

Launch Claude Code, Cursor, or your preferred AI coding agent.

Try It Out

Use the prompt template or examples below to test the skill.

Customize

Adapt the skill to your specific use case and workflow.

Usage Examples

📝

No Examples Available

Check the GitHub repository or documentation for usage examples.

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