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Basic Information

Grok CLI is a conversational AI command-line tool that brings Grok models into the terminal to assist with code and project tasks. It is designed to let users interact with an AI assistant that can read, create, and edit files, run shell commands, and choose tools automatically to accomplish multi-step workflows. The project provides both an interactive Ink-based terminal UI and a headless mode for scripting and automation. It supports configuration at user and project levels so defaults and per-project model choices are respected. The repository includes tooling to connect to OpenAI-compatible providers, optional Morph Fast Apply for high-speed edits, and MCP (Model Context Protocol) integrations for extending capabilities with external servers and services. Installation and development are Node.js-based with global npm install or local link workflows. Prerequisites include Node.js 16+ and an API key for Grok or compatible providers.

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Features
The README highlights several concrete features: a natural language conversational interface powered by Grok models, intelligent file operations where the AI views, creates, and edits files using editor tools, and bash integration that lets the assistant execute shell commands. Automatic tool selection allows the assistant to pick appropriate local tools and editors. Morph Fast Apply is optional for very fast, accurate multi-line code edits. MCP tools let users add subprocess, HTTP, or SSE-based servers to extend functionality and integrate services like Linear. The UI is built with Ink for an interactive terminal experience and the CLI supports headless mode for scripting and CI. Configuration is flexible with user-level and project-level JSON settings, and the CLI supports multiple API providers using OpenAI-compatible endpoints.
Use Cases
Grok CLI helps developers and power users by providing an AI companion inside the terminal that speeds common tasks such as code refactors, file creation, and repository exploration. In interactive mode it supports conversational workflows for debugging and editing, while headless mode enables automation in CI/CD pipelines, shell scripts, and batch processing. The assistant can run commands, limit tool execution rounds for resource control, and switch models per-project or per-invocation to balance cost and capability. MCP integrations enable project management and other external tooling to be controlled by the assistant. With optional Morph Fast Apply, complex edits and refactors become faster and more reliable. Overall the tool centralizes AI-driven code and file operations while keeping configuration and model selection flexible.

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