A curated directory of product CLIs, developer tools, and terminal apps — verified for humans, scripts, and AI agents.
>_$ bun
An all-in-one JavaScript runtime, package manager, bundler, and test runner.
>_$ wrangler
The official Cloudflare developer CLI for Workers, D1, R2, KV, Queues, Workflows, and more.
>_$ duckdb
Query local files and analytical datasets with an in-process SQL database.
>_$ ffmpeg
Record, convert, stream, inspect, and process audio and video.
>_$ gh
GitHub on the command line: repositories, pull requests, issues, Actions, releases, and API calls.
>_$ copilot
GitHub’s terminal coding agent for planning, editing, running, and reviewing changes with repository context.
>_$ glab
GitLab’s official CLI for merge requests, issues, pipelines, releases, snippets, and self-managed instances.
>_$ gws
One command line for Gmail, Drive, Calendar, Sheets, Docs, Chat, Admin, and the rest of Google Workspace.
>_$ http
A human-friendly HTTP client with JSON, sessions, auth, and formatted output.
>_$ k9s
A terminal UI for navigating, observing, and managing Kubernetes clusters.
>_$ llm
Run prompts, manage models, and extend LLM providers with plugins.
>_$ lark
The official Lark and Feishu CLI with commands for Messenger, Docs, Base, Sheets, Calendar, Mail, Tasks, and Meetings.
>_$ lazydocker
A terminal UI for Docker containers, services, images, logs, and stats.
>_$ lazygit
A keyboard-driven terminal UI for staging, rebasing, branching, and Git history.
>_$ neonctl
Manage Neon projects, Postgres branches, databases, roles, connection strings, and API keys.
>_$ ollama
Run and manage open models locally through a simple command-line interface.
>_$ playwright
Cross-browser end-to-end testing and browser automation from the command line.
>_$ slack
Create, run, test, and deploy Slack apps from the terminal with the official developer CLI.
>_$ snyk
Scan source code, dependencies, containers, and infrastructure as code for security vulnerabilities.
>_$ stripe
Build, test, and manage Stripe integrations, including local webhook forwarding and test events.
>_$ supabase
Run Supabase locally, manage database migrations, deploy Edge Functions, and generate database types.
>_$ vercel
Develop, preview, deploy, and manage Vercel projects and environment variables from the terminal.
>_$ yazi
An asynchronous terminal file manager with rich previews and plugins.
>_$ ast-grep
Search, lint, and rewrite code using syntax-aware structural patterns.
>_$ btop
A resource monitor for CPU, memory, disks, network, and processes.
>_$ fzf
A general-purpose fuzzy finder for files, history, processes, and more.
>_$ jq
A compact and expressive command-line processor for JSON data.
>_$ just
A convenient command runner for project-specific development recipes.
>_$ mise
Manage language runtimes, environment variables, and project tasks.
>_$ rg
Recursively search files with fast regex matching and gitignore support.
Common questions about CLI tools, Agent CLIs, and command line automation
A CLI, or command-line interface, lets you control software by typing commands in a terminal instead of clicking through a graphical interface. CLI tools are useful for development, automation, scripts, CI pipelines, and repeatable operations.
An Agent CLI is either a command-line tool for operating an AI agent or a conventional CLI designed to be called reliably by AI agents. Agent-friendly CLIs expose clear commands, non-interactive options, predictable output, and meaningful exit codes so an agent can plan, execute, and verify work.
Yes. AI coding agents can invoke many of these CLIs through a shell to work with repositories, cloud services, databases, productivity apps, and deployment systems. Tools marked Agent-ready are especially suitable for scripted or autonomous use, but authentication and permissions still need to be configured safely.
The best CLI tools for AI agents support non-interactive commands, stable flags, structured or parseable output, standard input and output, documented authentication, and reliable exit codes. These features make results easier for an agent to interpret and verify without manual intervention.
Choose an official CLI when you need first-party support, close alignment with a service API, and predictable updates. A community CLI can be a better fit when it offers a simpler workflow or capabilities the official tool lacks. Review its repository, maintenance activity, permissions, and installation instructions before use.
Use an OS keychain, environment variables, or a dedicated secret store instead of placing API keys in repositories, prompts, or shell history. Give people and AI agents least-privilege access, start in read-only or test environments, and confirm that automated commands support previews, explicit confirmation controls, and reliable exit codes.
