eLyiN/gemini-bridge
If you are the rightful owner of gemini-bridge and would like to certify it and/or have it hosted online, please leave a comment on the right or send an email to henry@mcphub.com.
Gemini Bridge is a lightweight MCP server that facilitates interaction between Claude Code and Google's Gemini AI using the official CLI.
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
š Quick Start
Prerequisites
-
Install Gemini CLI:
npm install -g @google/gemini-cli
-
Authenticate with Gemini:
gemini auth login
-
Verify installation:
gemini --version
Installation
šÆ 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
š 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 ā (Default)
- Cursor ā
- VS Code ā
- Windsurf ā
- Cline ā
- Void ā
- Cherry Studio ā
- Augment ā
- Roo Code ā
- Zencoder ā
- Any MCP-compatible client ā
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
ā Cursor Settings
ā MCP
ā 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 ā Advanced MCP Settings
- Add to
cline_mcp_settings.json
:
{
"mcpServers": {
"gemini-bridge": {
"command": "uvx",
"args": ["gemini-bridge"],
"env": {}
}
}
}
Void
Go to: Settings
ā MCP
ā Add MCP Server
{
"mcpServers": {
"gemini-bridge": {
"command": "uvx",
"args": ["gemini-bridge"],
"env": {}
}
}
}
Cherry Studio
- Navigate to Settings ā MCP Servers ā Add Server
- Fill in the server details:
- Name:
gemini-bridge
- Type:
STDIO
- Command:
uvx
- Arguments:
["gemini-bridge"]
- Name:
- Save the configuration
Augment
Using the UI:
- Click hamburger menu ā Settings ā 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 ā MCP Servers ā Edit Global Config
- Add to
mcp_settings.json
:
{
"mcpServers": {
"gemini-bridge": {
"command": "uvx",
"args": ["gemini-bridge"],
"env": {}
}
}
}
Zencoder
- Go to Zencoder menu (...) ā Tools ā 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!
āļø 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)
- Recommended: 120-300 seconds for large file analysis
- Invalid values: Fall back to 60 seconds with warning
š ļø Available Tools
consult_gemini
Direct CLI bridge for simple queries.
Parameters:
query
(string): The question or prompt to send to Geminidirectory
(string): Working directory for the query (default: current directory)model
(string, optional): Model to use - "flash" or "pro" (default: "flash")
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 Geminidirectory
(string): Working directory for the queryfiles
(list): List of file paths relative to the directorymodel
(string, optional): Model to use - "flash" or "pro" (default: "flash")
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"
)
š 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"]
)
šļø Architecture
Core Design
- CLI-First: Direct subprocess calls to
gemini
command - Stateless: Each tool call is independent with no session state
- Fixed Timeout: 60-second maximum execution time
- Simple Error Handling: Clear error messages with fail-fast approach
Project Structure
gemini-bridge/
āāā src/
ā āāā __init__.py # Entry point
ā āāā __main__.py # Module execution entry point
ā āāā mcp_server.py # Main MCP server implementation
āāā .github/ # GitHub templates and workflows
āāā pyproject.toml # Python package configuration
āāā README.md # This file
āāā CONTRIBUTING.md # Contribution guidelines
āāā CODE_OF_CONDUCT.md # Community standards
āāā SECURITY.md # Security policies
āāā CHANGELOG.md # Version history
āāā LICENSE # MIT license
š§ 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.
š 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
š¤ Contributing
We welcome contributions from the community! Please read our 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
š License
This project is licensed under the MIT License - see the file for details.
š Version History
See for detailed version history.
š 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.