A curated directory of product CLIs, developer tools, and terminal apps — verified for humans, scripts, and AI agents.
>_$ copilot
GitHub’s terminal coding agent for planning, editing, running, and reviewing changes with repository context.
>_$ llm
Run prompts, manage models, and extend LLM providers with plugins.
>_$ ollama
Run and manage open models locally through a simple command-line interface.
>_$ aichat
Chat with multiple AI providers, roles, sessions, tools, and local models.
>_$ aider
An open-source AI pair programmer that edits code in a local Git repository with many model providers.
>_$ q
AWS’s terminal assistant for coding, shell completion, natural-language workflows, and AWS development.
>_$ claude
Anthropic’s agentic coding tool for understanding codebases, editing files, and automating terminal workflows.
>_$ cn
Run Continue coding-agent workflows from terminals and CI environments.
>_$ fabric
Apply reusable AI patterns to summarization, extraction, and research tasks.
>_$ gemini
Google’s open-source terminal agent with Gemini models, tools, MCP support, and project context.
>_$ goose
An open-source extensible AI agent that installs, executes, edits, and tests through terminal tools and MCP.
>_$ hf
Authenticate with the Hugging Face Hub, download and upload models, manage repositories, and run jobs.
>_$ interpreter
Use natural language to run code and complete computer tasks locally.
>_$ codex
OpenAI’s coding agent for reading, changing, and running code directly from the terminal.
>_$ opencode
An open-source terminal coding agent with multiple model providers, sessions, tools, and LSP integration.
>_$ qwen
Qwen’s open-source terminal coding agent with repository tools, non-interactive mode, and MCP 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.
