Gemini Bridge

A lightweight MCP (Model Context Protocol) server that enables AI coding assistants to interact with Google's Gemini AI through the official CLI. Works with Claude Code, Cursor, VS Code, and other MCP-compatible clients. Designed for simplicity, reliability, and seamless integration.

✨ Features

Direct Gemini CLI Integration: Zero API costs using official Gemini CLI
Simple MCP Tools: Two core functions for basic queries and file analysis
Stateless Operation: No sessions, caching, or complex state management
Production Ready: Robust error handling with configurable 60-second timeouts
Minimal Dependencies: Only requires mcp>=1.0.0 and Gemini CLI
Easy Deployment: Support for both uvx and traditional pip installation
Universal MCP Compatibility: Works with any MCP-compatible AI coding assistant

🚀 Quick Start

Prerequisites

Install Gemini CLI:
```
npm install -g @google/gemini-cli
```
Authenticate with Gemini:
```
gemini auth login
```
Verify installation:
```
gemini --version
```

Installation

🎯 Recommended: PyPI Installation

# Install from PyPI
pip install gemini-bridge

# Add to Claude Code with uvx (recommended)
claude mcp add gemini-bridge -s user -- uvx gemini-bridge

Alternative: From Source

# Clone the repository
git clone https://github.com/shelakh/gemini-bridge.git
cd gemini-bridge

# Build and install locally
uvx --from build pyproject-build
pip install dist/*.whl

# Add to Claude Code
claude mcp add gemini-bridge -s user -- uvx gemini-bridge

Development Installation

# Clone and install in development mode
git clone https://github.com/shelakh/gemini-bridge.git
cd gemini-bridge
pip install -e .

# Add to Claude Code (development)
claude mcp add gemini-bridge-dev -s user -- python -m src

🌐 Multi-Client Support

Gemini Bridge works with any MCP-compatible AI coding assistant - the same server supports multiple clients through different configuration methods.

Supported MCP Clients

Claude Code ✅ (Default)
Cursor ✅
VS Code ✅
Windsurf ✅
Cline ✅
Void ✅
Cherry Studio ✅
Augment ✅
Roo Code ✅
Zencoder ✅
Any MCP-compatible client ✅

Configuration Examples

Claude Code (Default)

# Recommended installation
claude mcp add gemini-bridge -s user -- uvx gemini-bridge

# Development installation
claude mcp add gemini-bridge-dev -s user -- python -m src

Cursor

Global Configuration (~/.cursor/mcp.json):

{
  "mcpServers": {
    "gemini-bridge": {
      "command": "uvx",
      "args": ["gemini-bridge"],
      "env": {}
    }
  }
}

Project-Specific (.cursor/mcp.json in your project):

{
  "mcpServers": {
    "gemini-bridge": {
      "command": "uvx",
      "args": ["gemini-bridge"],
      "env": {}
    }
  }
}

Go to: Settings → Cursor Settings → MCP → Add new global MCP server

VS Code

Configuration (.vscode/mcp.json in your workspace):

{
  "servers": {
    "gemini-bridge": {
      "type": "stdio",
      "command": "uvx",
      "args": ["gemini-bridge"]
    }
  }
}

Alternative: Through Extensions

Open Extensions view (Ctrl+Shift+X)
Search for MCP extensions
Add custom server with command: uvx gemini-bridge

Windsurf

Add to your Windsurf MCP configuration:

{
  "mcpServers": {
    "gemini-bridge": {
      "command": "uvx",
      "args": ["gemini-bridge"],
      "env": {}
    }
  }
}

Cline (VS Code Extension)

Open Cline and click MCP Servers in the top navigation
Select Installed tab → Advanced MCP Settings
Add to cline_mcp_settings.json:

{
  "mcpServers": {
    "gemini-bridge": {
      "command": "uvx",
      "args": ["gemini-bridge"],
      "env": {}
    }
  }
}

Void

Go to: Settings → MCP → Add MCP Server

{
  "mcpServers": {
    "gemini-bridge": {
      "command": "uvx",
      "args": ["gemini-bridge"],
      "env": {}
    }
  }
}

Cherry Studio

Navigate to Settings → MCP Servers → Add Server
Fill in the server details:
- Name: gemini-bridge
- Type: STDIO
- Command: uvx
- Arguments: ["gemini-bridge"]
Save the configuration

Augment

Using the UI:

Click hamburger menu → Settings → Tools
Click + Add MCP button
Enter command: uvx gemini-bridge
Name: Gemini Bridge

Manual Configuration:

"augment.advanced": { 
  "mcpServers": [ 
    { 
      "name": "gemini-bridge", 
      "command": "uvx", 
      "args": ["gemini-bridge"],
      "env": {}
    }
  ]
}

Roo Code

Go to Settings → MCP Servers → Edit Global Config
Add to mcp_settings.json:

{
  "mcpServers": {
    "gemini-bridge": {
      "command": "uvx",
      "args": ["gemini-bridge"],
      "env": {}
    }
  }
}

Zencoder

Go to Zencoder menu (...) → Tools → Add Custom MCP
Add configuration:

{
  "command": "uvx",
  "args": ["gemini-bridge"],
  "env": {}
}

Hit the Install button

Alternative Installation Methods

For pip-based installations:

{
  "command": "gemini-bridge",
  "args": [],
  "env": {}
}

For development/local testing:

{
  "command": "python",
  "args": ["-m", "src"],
  "env": {},
  "cwd": "/path/to/gemini-bridge"
}

For npm-style installation (if needed):

{
  "command": "npx",
  "args": ["gemini-bridge"],
  "env": {}
}

Universal Usage

Once configured with any client, use the same two tools:

Ask general questions: "What authentication patterns are used in this codebase?"
Analyze specific files: "Review these auth files for security issues"

The server implementation is identical - only the client configuration differs!

⚙️ Configuration

Timeout Configuration

By default, Gemini Bridge uses a 60-second timeout for all CLI operations. For longer queries (large files, complex analysis), you can configure a custom timeout using the GEMINI_BRIDGE_TIMEOUT environment variable.

Example configurations:

Claude Code

# Add with custom timeout (120 seconds)
claude mcp add gemini-bridge -s user --env GEMINI_BRIDGE_TIMEOUT=120 -- uvx gemini-bridge

Manual Configuration (mcp_settings.json)

{
  "mcpServers": {
    "gemini-bridge": {
      "command": "uvx",
      "args": ["gemini-bridge"],
      "env": {
        "GEMINI_BRIDGE_TIMEOUT": "120"
      }
    }
  }
}

Timeout Options:

Default: 60 seconds (if not configured)
Range: Any positive integer (seconds)
Per-call override: Supply timeout_seconds to either tool for one-off extensions
Recommended: 120-300 seconds for large file analysis
Invalid values: Fall back to 60 seconds with warning

🛠️ Available Tools

`consult_gemini`

Direct CLI bridge for simple queries.

Parameters:

query (string): The question or prompt to send to Gemini
directory (string): Working directory for the query (default: current directory)
model (string, optional): Model to use - "flash" or "pro" (default: "flash")
timeout_seconds (int, optional): Override the execution timeout for this request

Example:

consult_gemini(
    query="Find authentication patterns in this codebase",
    directory="/path/to/project",
    model="flash"
)

`consult_gemini_with_files`

CLI bridge with file attachments for detailed analysis.

Parameters:

query (string): The question or prompt to send to Gemini
directory (string): Working directory for the query
files (list): List of file paths relative to the directory
model (string, optional): Model to use - "flash" or "pro" (default: "flash")
timeout_seconds (int, optional): Override the execution timeout for this request
mode (string, optional): Either "inline" (default) to stream file contents or "at_command" to let Gemini CLI resolve @path references itself

Example:

consult_gemini_with_files(
    query="Analyze these auth files and suggest improvements",
    directory="/path/to/project",
    files=["src/auth.py", "src/models.py"],
    model="pro",
    timeout_seconds=180
)

Tip: When scanning large trees, switch to mode="at_command" so the Gemini CLI handles file globbing and truncation natively.

📋 Usage Examples

Basic Code Analysis

# Simple research query
consult_gemini(
    query="What authentication patterns are used in this project?",
    directory="/Users/dev/my-project"
)

Detailed File Review

# Analyze specific files
consult_gemini_with_files(
    query="Review these files and suggest security improvements",
    directory="/Users/dev/my-project",
    files=["src/auth.py", "src/middleware.py"],
    model="pro"
)

Multi-file Analysis

# Compare multiple implementation files
consult_gemini_with_files(
    query="Compare these database implementations and recommend the best approach",
    directory="/Users/dev/my-project",
    files=["src/db/postgres.py", "src/db/sqlite.py", "src/db/redis.py"],
    mode="at_command"
)

Large File Safeguards

Inline transfers cap at ~256 KB per file and ~512 KB per request to avoid hangs.
Oversized files are truncated to head/tail snippets with a warning in the MCP response.
Tune the caps with environment variables (GEMINI_BRIDGE_MAX_INLINE_TOTAL_BYTES, etc.) or prefer mode="at_command" for bigger payloads.

🏗️ Architecture

Core Design

CLI-First: Direct subprocess calls to gemini command
Stateless: Each tool call is independent with no session state
Adaptive Timeout: Defaults to 60 seconds but overridable per request or via env var
Attachment Guardrails: Inline mode enforces lightweight limits; @ mode delegates to Gemini CLI tooling
Simple Error Handling: Clear error messages with fail-fast approach

Project Structure

gemini-bridge/
├── src/
│   ├── __init__.py              # Entry point
│   ├── __main__.py              # Module execution entry point
│   └── mcp_server.py            # Main MCP server implementation
├── .github/                     # GitHub templates and workflows
├── pyproject.toml              # Python package configuration
├── README.md                   # This file
├── CONTRIBUTING.md             # Contribution guidelines
├── CODE_OF_CONDUCT.md          # Community standards
├── SECURITY.md                 # Security policies
├── CHANGELOG.md               # Version history
└── LICENSE                    # MIT license

🔧 Development

Local Testing

# Install in development mode
pip install -e .

# Run directly
python -m src

# Test CLI availability
gemini --version

Integration with Claude Code

The server automatically integrates with Claude Code when properly configured through the MCP protocol.

🔍 Troubleshooting

CLI Not Available

# Install Gemini CLI
npm install -g @google/gemini-cli

# Authenticate
gemini auth login

# Test
gemini --version

Connection Issues

Verify Gemini CLI is properly authenticated
Check network connectivity
Ensure Claude Code MCP configuration is correct
Check that the gemini command is in your PATH

Common Error Messages

"CLI not available": Gemini CLI is not installed or not in PATH
"Authentication required": Run gemini auth login
"Timeout after 60 seconds": Query took too long, try breaking it into smaller parts

🤝 Contributing

We welcome contributions from the community! Please read our Contributing Guidelines for details on how to get started.

Quick Contributing Guide

Fork the repository
Create a feature branch
Make your changes
Add tests if applicable
Submit a pull request

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🔄 Version History

See CHANGELOG.md for detailed version history.

🆘 Support

Issues: Report bugs or request features via GitHub Issues
Discussions: Join the community discussion
Documentation: Additional docs can be created in the docs/ directory

Focus: A simple, reliable bridge between Claude Code and Gemini AI through the official CLI.

Name		Name	Last commit message	Last commit date
Latest commit History 21 Commits
.github		.github
src		src
tests		tests
.gitignore		.gitignore
AGENTS.md		AGENTS.md
CHANGELOG.md		CHANGELOG.md
CLAUDE.md		CLAUDE.md
CODE_OF_CONDUCT.md		CODE_OF_CONDUCT.md
CONTRIBUTING.md		CONTRIBUTING.md
LICENSE		LICENSE
README.md		README.md
SECURITY.md		SECURITY.md
pyproject.toml		pyproject.toml

License

eLyiN/gemini-bridge

Folders and files

Latest commit

History

Repository files navigation