Google has announced Gemini CLI, a new open-source AI tool designed specifically to integrate seamlessly within developers’ existing terminal workflows. Gemini CLI runs locally, allowing users to interact naturally with their local codebases through Google’s Gemini AI models. With this tool, developers can easily make requests in plain language—for instance, asking Gemini CLI to clarify complicated sections of code, implement new features, debug issues, or execute commands.
This latest release represents Google’s intensified efforts to deepen the integration of its AI models within everyday developer tasks. The company’s growing suite of AI coding features already includes established products such as Gemini Code Assist and the asynchronous AI coding assistant known as Jules. Gemini CLI now positions Google directly against established command-line offerings such as OpenAI’s Codex CLI and Anthropic’s Claude Code—both noted for their speed, efficiency, and ease of integration.
Google’s Gemini 2.5 Pro model, launched in April, quickly rose in popularity, prompting a surge of third-party AI-powered developer tools like Cursor and GitHub Copilot. In response, Google aims to forge stronger direct relationships with developers by presenting in-house, tailored products such as Gemini CLI.
While primarily intended for coding tasks, Gemini CLI also handles multiple other functions. Google indicates that the tool can support video creation through the Veo 3 model, help produce comprehensive research reports via its Deep Research agent, and provide access to real-time data through integration with Google Search. Additionally, Gemini CLI offers connectivity to external MCP servers, extending its reach to external databases.
To further drive adoption and developer participation, Google is open-sourcing Gemini CLI under the widely permissive Apache 2.0 license. The company anticipates active contributions from the broader developer community via GitHub.
As part of its rollout strategy, Google is offering generous free usage allowances. Developers adopting Gemini CLI will receive access to 60 model requests per minute and up to 1,000 requests per day. According to the company, this allocation significantly exceeds average developer usage patterns, making the tool appealing for routine, extensive use.
Despite growing popularity, existing AI-coding solutions have faced skepticism within the developer community regarding accuracy and reliability—recent surveys reveal fewer than half of developers fully trust code generated by AI. Research has also shown occasional errors or overlooked security issues arising from AI-produced code, highlighting ongoing challenges developers must consider as they adopt new AI tools into their workflow.
