
Google has officially launched Gemini CLI, a new open-source AI tool designed to bring its Gemini model into developers’ command-line workflows. This innovative AI agent offers seamless integration with the terminal, enabling direct access to Gemini from the prompt. Although it excels at code generation, the company notes that Gemini CLI is also built for broader applications like research, task management, and content creation.
Moreover, Gemini CLI links with Gemini Code Assist, allowing users on free, standard, and enterprise tiers to benefit from AI-first coding support in both VS Code and the terminal. According to Google, this combination offers a comprehensive and flexible coding solution. Because it is local and lightweight, developers can quickly interact with the model without the overhead of switching platforms.
Since the CLI tool is open source under the Apache 2.0 license, developers can review its architecture, customize functions, and inspect the security framework behind its operations. This level of transparency ensures trust and adaptability in diverse environments.
High Limits, Free Access, and Powerful Integration
Gemini CLI comes with generous usage allowances. After logging in with a personal Google account, users receive a free Gemini Code Assist license, granting access to Gemini 2.5 Pro and its extended one million-token context. In addition, Google is offering 60 requests per minute and up to 1,000 per day for free, making it one of the most accessible tools of its kind.
For those needing more scale such as professionals running multiple agents Google supports usage-based billing via AI Studio or Vertex AI. Alternatively, developers can upgrade to a Standard or Enterprise Code Assist license.
With these features in place, Gemini CLI supports code writing, file handling, command execution, and even dynamic debugging. Consequently, it turns the command line into a smart assistant that reacts to natural language inputs.
Extendable and Script-Friendly by Design
Gemini CLI includes built-in tools that enhance its performance. For example, developers can issue ground prompts using Google Search, fetch real-time web data, or expand the toolset via bundled extensions and Model Context Protocol (MCP) support. In addition, it can run in non-interactive modes, making it script-friendly and ideal for workflow automation.
Because of its open-source nature, developers are also encouraged to tailor the AI’s responses and behavior. Custom prompts and instructions allow Gemini CLI to adapt to specific projects or organizational standards. As a result, it becomes more than just a productivity booster it evolves into a core component of a developer’s workflow.