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github/copilot-cli

10,460ShellAudience · developerComplexity · 2/5Setup · moderate

TLDR

GitHub Copilot's official command-line AI coding assistant that lets you build, debug, and refactor code using plain-English requests directly in your terminal, requires an active paid GitHub Copilot subscription.

Mindmap

mindmap
  root((Copilot CLI))
    What it does
      Terminal AI agent
      Code changes
      Repo queries
    Features
      Multi-step planning
      Human approval step
      MCP extensions
      GitHub integration
    Installation
      Homebrew macOS
      curl Linux
      WinGet Windows
      npm cross-platform
    Requirements
      Copilot subscription
      GitHub account
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Code map

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filefunction / class

Things people build with this

USE CASE 1

Ask the AI to refactor or add a feature to your codebase in natural language without leaving the terminal.

USE CASE 2

Query your GitHub issues and pull requests in plain English directly from the command line.

USE CASE 3

Extend the CLI with MCP plugins to connect the AI agent to custom data sources or internal tools.

USE CASE 4

Debug a failing test by describing the error in plain English and reviewing the proposed fix before it runs.

Tech stack

ShellMCPLanguage Server Protocol

Getting it running

Difficulty · moderate Time to first run · 30min

Requires an active paid GitHub Copilot subscription, must authenticate with a GitHub account before first use.

In plain English

GitHub Copilot CLI is an AI-powered coding assistant that runs directly in your terminal. Instead of opening a browser or switching to a separate app, you type natural language requests in your command line and an AI agent helps you build, debug, understand, and refactor code. It works on Linux, macOS, and Windows. The tool requires an active GitHub Copilot subscription, which is a paid service from GitHub. Once installed and authenticated with your GitHub account, you launch it by typing copilot in any folder containing code you want to work with. From there you can have a conversation with the AI about your code, ask it to make changes, or get explanations of what existing code does. A key feature is that nothing runs automatically without your approval. The agent can plan and propose multi-step changes, but you review each action before it executes. It also comes connected to GitHub's own infrastructure by default, so it can access your repositories, issues, and pull requests using plain language. The CLI supports extending its capabilities through a standard called MCP (Model Context Protocol), which lets you plug in additional tools or data sources beyond what ships in the box. It also has optional support for Language Server Protocol, which is a way to give the AI more precise understanding of code in specific programming languages by connecting it to a language analysis tool you install separately. Installation is straightforward on all platforms: a one-line curl command on Mac and Linux, Homebrew, WinGet on Windows, or npm. The default AI model is Claude Sonnet, but you can switch models using a command inside the tool. The project is actively developed, with frequent updates, and the GitHub team is collecting feedback through the repository's issue tracker.

Copy-paste prompts

Prompt 1
I've installed GitHub Copilot CLI and I'm in a Python project directory. Write me a prompt to ask it to add input validation to a specific function.
Prompt 2
How do I add a custom MCP tool to GitHub Copilot CLI so the AI agent can query my internal API during coding sessions?
Prompt 3
I want to use GitHub Copilot CLI to get a high-level overview of an unfamiliar codebase. What sequence of prompts should I use?
Prompt 4
Walk me through switching the default AI model in GitHub Copilot CLI from Claude Sonnet to a different supported model.
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