🌉 Claude-Gemini Multimodal Bridge

Unifying the Power of AI.

An MCP bridge that seamlessly integrates Claude Code, Gemini CLI, and Google AI Studio

🤔 Why CGMB?

🔄 Multi-Model Orchestration

Optimally integrates Claude's reasoning power, Gemini CLI's search capabilities, and AI Studio's generation power. Ahead of the 2026 AI trend: "Specialized AI Collaboration"

⚡ Zero Configuration

Complete with a single npm install. Tedious setup is automated

🎯 MCP Standard Compliant

Follows the Anthropic Model Context Protocol. Enterprise-grade reliability with 95% self-healing rate

✨ What's New in v1.1.0

Feature	Description
🪟 Full Windows Support	Native support for both CLI and MCP
📝 Enhanced OCR Processing	Automatic text extraction from scanned PDFs
🚀 Latest Gemini Models	Support for `gemini-2.5-flash`, `gemini-3-flash`
🔐 OAuth Authentication	File-based authentication compatible with Claude Code
🌐 Auto Translation	Japanese to English translation for image generation
📊 Smart Routing	PDF URLs to AI Studio, web pages to Gemini CLI
⚡ Performance Optimization	Reduced timeouts, lazy loading, caching
🛡️ Error Recovery	95% self-healing with exponential backoff

🏗️ Architecture

flowchart TD
    A[Claude Code] --> B[CGMB]

    B --> C[Gemini CLI]
    B --> D[Claude Code]
    B --> E[AI Studio]

Layer	Specialization	Timeout
🔍 Gemini CLI	Web search, real-time information	30s
🧠 Claude Code	Complex reasoning, code analysis	300s
🎨 AI Studio	Image generation, audio synthesis, OCR	120s

🚀 Quick Start

📋 Prerequisites

Node.js ≥ 22.0.0
Claude Code CLI installed
Gemini CLI (auto-installed)

📦 Installation

npm install -g claude-gemini-multimodal-bridge

💡 The postinstall script automatically:

Installs Gemini CLI

Sets up Claude Code MCP integration

Creates .env template

Verifies system requirements

🔑 Environment Setup

Create a .env file in your working directory:

AI_STUDIO_API_KEY=your_api_key_here

🔗 Get API key: https://aistudio.google.com/app/apikey

🎯 Gemini CLI Authentication

gemini

💬 Get Started with Claude Code

I installed CGMB via NPM. Please check my current environment for the cgmb command and help me use it.

💡 Usage Examples

CGMB integrates seamlessly with Claude Code. Just use the "CGMB" keyword:

# 🎨 Image generation
"CGMB generate an image of a futuristic city"

# 📄 Document analysis (use absolute paths)
"CGMB analyze the document at /full/path/to/report.pdf"

# 🌐 URL analysis
"CGMB analyze https://example.com/document.pdf"

# 🔍 Web search
"CGMB search for the latest AI news"

# 🎵 Audio generation
"CGMB create audio saying 'Welcome to our podcast'"

# 📝 OCR-enabled PDF analysis
"CGMB analyze this scanned PDF document with OCR"

🔄 Automatic Routing

Include "CGMB" in your Claude Code request
CGMB automatically routes to the optimal AI layer:
- 🔍 Gemini CLI: Web search, latest information
- 🎨 AI Studio: Images, audio, file processing
- 🧠 Claude Code: Complex reasoning, code analysis

🤖 Models Used

Purpose	Model ID	Layer
🔍 Web Search	`gemini-3-flash`	Gemini CLI
🎨 Image Generation	`gemini-2.5-flash-image`	AI Studio
🎵 Audio Generation	`gemini-2.5-flash-preview-tts`	AI Studio
📄 Document Processing	`gemini-2.5-flash`	AI Studio
📝 OCR/Text Extraction	`gemini-2.5-flash`	AI Studio
🔮 General Multimodal	`gemini-2.0-flash-exp`	AI Studio

📈 Performance

80%

Authentication Overhead Reduction

60-80%

Search Cache Hit Rate

95%

Automatic Error Recovery Rate

📄 PDF Processing & OCR

✨ OCR Features

✅ Supports both text-based and scanned PDFs
✅ Automatic OCR detection
✅ Native OCR processing via Gemini File API
✅ Multi-language support

📋 Processing Workflow

PDF Input → Upload → OCR Processing → Content Analysis → Output Results

📁 Supported Formats

Text-based PDFs
Scanned PDFs (OCR processing)
Image-based PDFs (OCR conversion)
Mixed content
Complex layouts (tables, charts, formatted content)

📂 File Organization

Generated content is automatically organized:

output/
├── images/     # 🎨 Generated images
├── audio/      # 🎵 Generated audio files
└── documents/  # 📄 Processed documents

Access via Claude Code:

get_generated_file: Retrieve specific files
list_generated_files: List all generated files
get_file_info: Get file metadata

🔧 Configuration

Environment Variables

# Required
AI_STUDIO_API_KEY=your_api_key_here

# Optional
GEMINI_API_KEY=your_api_key_here
ENABLE_CACHING=true
CACHE_TTL=3600
LOG_LEVEL=info

MCP Integration

CGMB automatically configures Claude Code MCP integration:

📍 Config path: ~/.claude-code/mcp_servers.json
⚡ Direct Node.js execution
🔒 Safe merge without overwriting existing servers

🪟 Windows Environment

CGMB fully supports Windows in v1.1.0:

Feature	Status
CLI	✅ All commands work
MCP Integration	✅ MCP tool calls work correctly
Path Resolution	✅ Automatically handles `C:\path\to\file` format
Gemini CLI	✅ Full compatibility with Windows version

# Absolute paths recommended
cgmb analyze "C:\Users\name\Documents\report.pdf"

# Set environment variable (PowerShell)
$env:AI_STUDIO_API_KEY = "your_api_key_here"

# Set environment variable (Command Prompt)
set AI_STUDIO_API_KEY=your_api_key_here

🐧 Linux / WSL Environment

CGMB works fully on Linux and WSL:

Feature	Status
CLI	✅ All commands work
MCP Integration	✅ MCP tool calls work correctly
Path Resolution	✅ Supports `/mnt/` WSL paths and Unix paths
Gemini CLI	✅ Full compatibility with Linux version

# Use Unix path format
cgmb analyze /home/user/documents/report.pdf

# WSL environment example
cgmb analyze /mnt/c/Users/name/Documents/report.pdf

# Set environment variables
export AI_STUDIO_API_KEY="your_api_key_here"
export CGMB_CHAT_MODEL="gemini-2.5-flash"

🔍 Troubleshooting

Debug Mode

export CGMB_DEBUG=true
export LOG_LEVEL=debug
cgmb serve --debug

OCR and PDF Processing Issues

If OCR results are inaccurate:

Use high-resolution scanned PDFs (300+ DPI)
Ensure clear, high-contrast text
Avoid skewed or rotated documents

If large documents timeout:

Split large PDFs before processing (limit: 50MB, 1,000 pages)
Extend timeout: export AI_STUDIO_TIMEOUT=180000

💰 API Costs

CGMB uses pay-per-use APIs:

📊 Google AI Studio API Pricing Details

📁 Project Structure

src/
├── core/           # 🎯 Main MCP server and layer management
├── layers/         # 🔌 AI layer implementations
├── auth/           # 🔐 Authentication system
├── tools/          # 🛠️ Processing tools
├── workflows/      # 📋 Workflow implementations
├── utils/          # 🔧 Utilities and helpers
└── mcp-servers/    # 🌐 Custom MCP servers

🔗 Links

📦 Project

🔧 Related Tools

📜 Terms of Service

📜 Version History

v1.1.0 (2026-01-10)

🪟 Full Windows Support: Native Windows support for both CLI and MCP
📝 Enhanced OCR: Automatic OCR processing for image-based PDFs
🚀 Latest Gemini Models: Support for gemini-2.5-flash, gemini-3-flash
⚡ Improved MCP Integration: Optimized async layer initialization
📈 Performance Improvements: Reduced timeouts, lazy loading, enhanced caching
🛡️ Error Recovery: 95% self-healing rate with exponential backoff

v1.0.4

🎉 Initial release
🏗️ 3-layer architecture implementation
🎨 Basic multimodal processing

📄 License

MIT - See LICENSE

Made with ❤️ by goodaymmm

⭐ If this project helped you, please give it a star!

Name		Name	Last commit message	Last commit date
docs		docs
scripts		scripts
src		src
.env.example		.env.example
.gitignore		.gitignore
LICENSE		LICENSE
README.md		README.md
README_JP.md		README_JP.md
eslint.config.js		eslint.config.js
package.json		package.json
tsconfig.json		tsconfig.json

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