Gemini CLI

Gemini CLI is an open-source AI agent from Google that brings Gemini directly into the terminal. Instead of switching between your editor, browser, and chat tools, you can ask Gemini CLI to understand code, explain files, automate tasks, and help with development work right from the command line.

It is designed mainly for developers, but it can also help with research, file management, documentation, and workflow automation. If you like working in a terminal and want AI assistance close to your project files, Gemini CLI is a practical tool to explore.

What is Gemini CLI?

Gemini CLI is a terminal-based AI assistant developed by Google and published as an open-source project. It connects Gemini models to your local workflow, allowing you to chat with the model, inspect codebases, generate or edit files, run shell commands with permission, and use built-in tools such as web fetching and search.

Google also describes Gemini CLI as the engine behind Gemini Code Assist agent mode in VS Code, which shows that it is built with real software development use cases in mind. The tool supports local and remote MCP servers as well, which makes it more flexible for advanced integrations and custom workflows.

Who is Gemini CLI for?

Gemini CLI is best suited for developers, engineers, technical teams, and advanced users who spend a lot of time in the command line. It is especially useful for people who want to inspect repositories, generate code, debug problems, summarize project changes, or automate repetitive development tasks.

It can also be helpful for technical writers, DevOps users, and power users who want to work with files, scripts, and project folders using natural language prompts.

Main features

One of the biggest strengths of Gemini CLI is code understanding. You can ask it to explain a codebase, summarize changes, generate new code, or help troubleshoot bugs in plain language. This makes it useful both for new projects and for understanding older or unfamiliar repositories.

Another standout feature is tool use. Gemini CLI can work with files, run shell commands after approval, fetch web content, and use Google Search grounding for more current information. This gives it more practical value than a simple text chatbot.

It also supports multimodal workflows. Google says Gemini CLI can generate apps from PDFs, images, or sketches, which opens the door to faster prototyping and project scaffolding.

For teams and advanced users, Gemini CLI supports MCP integrations, scripting, and GitHub workflows. It can run non-interactively in scripts, output JSON for automation, and connect with GitHub Actions for tasks like pull request reviews, issue triage, and on-demand assistance.

Another helpful feature is checkpointing. Before AI-powered file changes are made, Gemini CLI can save a snapshot of your project state so you can restore it later if needed. That adds a useful safety layer when experimenting with edits.

Common use cases

Gemini CLI fits a wide range of developer workflows. A common use case is asking it to analyze a project and explain how the code is structured. This is helpful when joining a new team, reviewing an open-source repository, or revisiting an old codebase.

It is also useful for code generation and debugging. You can ask it to build a component, write a script, improve tests, or investigate an error. Because it works in the terminal and can inspect local files, its responses can be more grounded in your actual project context.

Another use case is automation. Gemini CLI can run in scripts with prompt-based commands and structured JSON output, making it useful for repeatable internal workflows. Teams can also use it in GitHub-centered processes such as pull request review support and issue handling.

Outside coding, it can help rename files based on content, combine data from files, summarize documents, and perform research tasks that benefit from terminal-based AI assistance.

How to use Gemini CLI

Getting started is fairly straightforward. Google provides several installation methods, including npm, Homebrew, MacPorts, and an Anaconda-based setup for restricted environments. For most users, the standard install command is through npm, after which you launch it with the simple command to start a session.

After installation, you need to authenticate. The easiest option is signing in with a Google account. Gemini CLI also supports using a Gemini API key for more direct model control and usage-based billing, or Vertex AI for enterprise and production environments.

Once authenticated, you can open Gemini CLI in your current directory and begin prompting it in natural language. For example, you can ask it to explain your codebase, summarize changes, generate a feature, or inspect files in your project folder. If it needs to read files or run commands, it can ask for approval before taking action.

Gemini CLI also supports non-interactive usage for automation. You can pass a prompt directly in the command line and request JSON output, which is helpful for scripts, tooling, and workflow pipelines.

Supported platforms

Gemini CLI works in terminal environments and can be installed through tools commonly used on macOS and Linux, including Homebrew and MacPorts. It is also available through npm, which makes it broadly usable anywhere Node.js-based CLI tools are supported. Google documentation also notes that shell execution uses bash on Linux and macOS, and PowerShell on Windows unless overridden, which indicates Windows support too.

In addition, Gemini CLI is available in Google Cloud Shell without extra setup, and part of its functionality is also surfaced through Gemini Code Assist in VS Code.

Pricing

Gemini CLI uses a freemium model. Google offers free usage options for individuals signing in with a Google account, including published request limits, and also provides a free tier when using a Gemini API key. For users who need more control or higher usage, Gemini CLI can work with usage-based Gemini API billing, paid Gemini Code Assist plans, Google AI Pro or Ultra higher limits, and Vertex AI for enterprise workloads.

That means new users can try Gemini CLI for free, while teams and heavier users have upgrade paths if they need more capacity, enterprise features, or broader production usage.

Integrations and ecosystem

A major advantage of Gemini CLI is that it is not limited to basic prompting. It supports MCP servers for custom tools and integrations, which can connect the CLI to outside services and internal systems. Google’s examples include workflows tied to services like GitHub, Slack, and databases through MCP tooling.

It also integrates with GitHub workflows through an official GitHub Action, making it easier to add AI help into code review and issue management processes. For developers already working in Google’s ecosystem, the connection to Gemini Code Assist and Vertex AI is another strong plus.

Why Gemini CLI stands out

Gemini CLI stands out because it combines AI assistance, terminal-native workflows, practical tool use, and open-source flexibility in one package. Rather than acting like a standalone chat app, it is designed to help you do real work inside your development environment.

Its combination of project-aware coding help, file and shell access, automation support, multimodal input, and integration options makes it one of the more capable AI terminal assistants available right now. For developers who prefer working close to their code and infrastructure, that is a meaningful advantage.

Final thoughts

If you want an AI coding and automation assistant that lives in the terminal, Gemini CLI is well worth a look. It is especially useful for developers who want fast access to code understanding, task automation, and project-aware help without leaving the command line.

The free entry point makes it easy to test, while the broader Google ecosystem gives it room to scale from personal use to team and enterprise workflows. If your daily workflow already revolves around the terminal, Gemini CLI can fit in naturally and help you move faster.