Google has finally made its serious entry into the AI coding tools market. They've released a CLI tool that offers virtually identical functionality to Claude Coder—and it's completely free. This isn't just another tool launch; it's Google's direct response to Claude's success.
Why Google is Going on the Offensive
With Claude Coder gaining tremendous traction among developers, Google's rapid response is fascinating to watch. Claude Coder's ability to implement complex features like Photoshop functionality has sent shockwaves through the industry.
Google's aggressive move highlights just how strategically important the AI coding tools market has become. These tools can revolutionize developer productivity and potentially reshape the entire software development paradigm—making them absolutely critical technology to control.
Installation and Basic Usage
One of Gemini CLI's biggest advantages is its incredibly simple installation process. Unlike Claude, which is Linux-only and requires WSL, Gemini CLI is built on Node.js and runs smoothly on any operating system.
```bash
npm install -g @google/gemini-cli
```
Just one command line installs it globally, and typing `gemini` launches it immediately. The initial setup only requires logging into your Google account and granting permissions—that's it.
The workspace concept is intuitive too. Your current folder automatically becomes the working directory, and all file creation and management centers around this folder. It's a very practical approach for project management.
Memory System and MCP Integration
One of Gemini CLI's interesting features is its memory system using markdown files. This file serves as the AI's memory bank for current work status, project characteristics, and future plans. You can view the entire contents with `/memory show` and update it with `/memory refresh`.
MCP (Model Context Protocol) integration is also supported. With the browsing MCP, the AI can actually open browsers and perform debugging on its own. If you're already using MCP with Claude Desktop, you can simply copy your configuration file and paste it into Gemini's settings file.
The configuration file is located at `C:\Users\[username]\.gemini\settings.json`. After adding MCP settings here, you can check installed MCP lists with the `/mcp` command.
Real Performance Comparison: Implementing Photoshop Features
Testing Gemini CLI with the same task as Claude Coder revealed some interesting differences. For implementing 10 Photoshop features, Gemini CLI completed the initial coding in about 4 minutes. It was impressive that it created only 3 files, implementing everything with minimal code.
However, the quality details left much to be desired. It had relatively fewer features and the design quality was inferior to Claude's. Particularly, its ability to execute external tools like automatic web server launching was weak, requiring manual server startup.
The bigger issue emerged during error correction. Fixing one error would create new problems elsewhere—a frustrating pattern that repeated constantly. While initial coding was fast, error correction ended up taking considerable time.
MCP Usage: Limitations and Potential
MCP usage also revealed inexperience. It frequently missed parameters or misused specific functions. This is crucial functionality for an AI agent, but it's not yet as stable as Claude.
However, it showed different capabilities when working with Sheriff Task Manager MCP. During initialization, it analyzed existing code status, and when tasks were registered, it created detailed plans and broke them down into smaller tasks. While it consumed tokens, the current free allowance is generous enough for over 2 hours of usage.
Strategies for Complex Tasks
For complex coding tasks, several strategies are essential:
Build Logging Systems: You need to track which file and which section caused problems when errors occur.
Apply MVC Model: Clearly separate code by roles and design each function to perform only one task.
Ask Repeatedly: Asking multiple questions about the same task effectively encourages the AI to think more deeply.
These strategies will become valuable know-how for all AI coding tools, not just Gemini CLI.
Diverse Usage Possibilities
Gemini CLI can handle much more than just coding. It can analyze images, text files, and PDF files. You can drag and drop files and ask questions to get detailed explanations. However, it's limited to processing files within the working folder only.
Using the `@` symbol shows the current folder's file list, and you can select specific files for questions. Typing `@.` provides a useful summary of all files in the current folder.
While it doesn't directly support image or video generation, integration with external tools through MCP should make this possible.
Conclusion: The Competition Begins
From hands-on experience, Claude Coder still feels more stable and polished, backed by accumulated expertise. However, Google's Gemini CLI is definitely worth exploring, especially while it's free.
The generous context capacity and cross-platform Node.js support are clear advantages. Google's aggressive market entry acknowledges the importance of the AI coding tools market, which means more choices for developers and quality improvements through competition.
The smart approach would be to experiment with various projects during the free period, understand each tool's strengths and weaknesses, and choose the tool that fits your development style. The era of AI coding tools competition has officially begun.