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gemini-cli-bridge
by Raudbjorn
⭐ 0🍴 0📅 2026年1月25日
SKILL.md
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
| Feature | Claude Code | Gemini CLI |
|---|---|---|
| Search | Web search tool | Native Google Search |
| Context | 200K tokens | 1M tokens |
| Free Tier | API key required | 1000 req/day free |
| Strengths | Coding, analysis | Search, multimodal |
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 CLIgemini_prompt_with_input- Send prompt with piped contentgemini_search- Use Google Search groundinggemini_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
| Variable | Description |
|---|---|
GOOGLE_API_KEY | API key for usage-based billing |
GEMINI_SYSTEM_MD | Path to custom system prompt |
Best Practices
- Specify Working Directory: Always set
working_dirfor file operations - Use YOLO Sparingly: Only enable for trusted, safe operations
- Leverage Search: Gemini excels at queries needing real-time info
- Check Token Stats: Monitor cached tokens for cost optimization
- Sandbox Mode: Use
sandbox: truefor 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
geminiinteractively to authenticate with Google - Rate Limit: Free tier allows 60 req/min, 1000 req/day
- Timeout: Increase
timeout_secsfor complex tasks
Authentication
Gemini CLI supports multiple auth methods:
-
Personal Google Account (recommended for personal use)
- Run
geminiand select "Login with Google" - 1000 requests/day free
- Run
-
Google AI Studio API Key
export GOOGLE_API_KEY="your-key" -
Vertex AI (for enterprise)
export GOOGLE_API_KEY="your-key" export GOOGLE_GENAI_USE_VERTEXAI=true
スコア
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50/100
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