name: gemini-cli-bridge description: Integrate with Google's Gemini CLI for delegating tasks to Gemini. Use when you need an alternative AI perspective, Google Search grounding, parallel task execution, or want to leverage Gemini's 1M token context window. Enables "Claude calling Gemini" patterns for diverse AI collaboration.

Gemini CLI Bridge

Delegate tasks to Google's Gemini CLI from any context.

When to Use

• Google Search Grounding: Gemini has native Google Search integration
• Alternative Perspective: Get a different AI's take on a problem
• Large Context: Gemini 2.5 Pro has a 1M token context window
• Parallel Work: Have Gemini work on a subtask while you continue
• Code Review: Cross-AI code review for better coverage

Key Differences from Claude Code

Usage Patterns

Via MCP Server (Recommended)

If the gemini-cli-mcp server is configured, use the MCP tools:

Use gemini_prompt to ask Gemini: "What are the latest developments in WebGPU?"

Tools available:

• gemini_prompt - Send a prompt to Gemini CLI
• gemini_prompt_with_input - Send prompt with piped content
• gemini_search - Use Google Search grounding
• gemini_version - Get version info

Via CLI (Direct)

Execute Gemini CLI directly:

# Single prompt
gemini -p "Explain this error message" --output-format json

# Pipe input
cat error.log | gemini -p "Analyze these errors"

# With Google Search
gemini -p "What's the current price of Bitcoin?"

# YOLO mode (auto-approve all actions)
gemini -p "Fix all linting errors" --yolo

Via Rust Library

use gemini_cli_rs::GeminiCliClient;

let client = GeminiCliClient::new()?;
let response = client.prompt("Analyze this codebase").await?;
println!("{}", response.text());

Configuration

MCP Server Setup

Add to Claude Desktop's claude_desktop_config.json:

{
  "mcpServers": {
    "gemini": {
      "command": "npx",
      "args": ["@svnbjrn/gemini-cli-mcp"]
    }
  }
}

Environment Variables

Best Practices

1. Specify Working Directory: Always set working_dir for file operations
2. Use YOLO Sparingly: Only enable for trusted, safe operations
3. Leverage Search: Gemini excels at queries needing real-time info
4. Check Token Stats: Monitor cached tokens for cost optimization
5. Sandbox Mode: Use sandbox: true for safer execution

Example Workflows

Current Events Research

I'll use Gemini for real-time search:

[gemini_search]
query: "What companies announced layoffs this week?"

Cross-AI Code Review

Let me get Gemini's perspective on this code:

[gemini_prompt_with_input]
prompt: "Review this code for bugs and suggest improvements"
stdin_input: "<paste code here>"

Large File Analysis

Gemini can handle larger context:

[gemini_prompt]
prompt: "Analyze the architecture of this entire codebase"
working_dir: "/home/user/large-project"

Parallel Documentation

[gemini_prompt]
prompt: "Generate API documentation for all public functions in src/"
working_dir: "/home/user/project"
yolo_mode: true

Error Handling

• Not Found: Install with npm install -g @google/gemini-cli
• Auth Failed: Run gemini interactively to authenticate with Google
• Rate Limit: Free tier allows 60 req/min, 1000 req/day
• Timeout: Increase timeout_secs for complex tasks

Authentication

Gemini CLI supports multiple auth methods:

1. Personal Google Account (recommended for personal use)

   • Run gemini and select "Login with Google"
   • 1000 requests/day free

2. Google AI Studio API Key

   export GOOGLE_API_KEY="your-key"
   

3. Vertex AI (for enterprise)

   export GOOGLE_API_KEY="your-key"
   export GOOGLE_GENAI_USE_VERTEXAI=true