Gemsuite (Google Gemini)

🚀 GemSuite-MCP Server

GemSuite-MCP is a powerful Gemini server based on the Model Context Protocol (MCP), specifically designed for integrating Google Gemini models. It offers intelligent model selection, advanced file processing, and seamless integration with multiple development environments.

🚀 Quick Start

GemSuite-MCP is a robust server built upon the Model Context Protocol (MCP), tailored for integrating Google Gemini models. It provides a range of features including intelligent model selection, advanced file processing, and seamless integration with various development environments.

✨ Features

• Optimal Gemini MCP Service: Offers high-performance integration of Gemini models.
• Model Context Protocol (MCP) Integration: Utilizes the MCP standard for efficient context transfer.
• Gemini API Tools: Provides dedicated tools for handling the Gemini API.
• Intelligent Model Selection: The system automatically selects the most suitable model for the task.
• Advanced File Processing: Supports various file operations such as analyzing, extracting, and simplifying content.
• Claude MCP Integration: Seamlessly combines with Claude's powerful inference capabilities.
• Gemini Search MCP: Enables efficient Gemini-based search functionality.
• Gemini Inference: Offers professional Gemini inference services.
• MCP Development Environment Integration: Supports direct integration with development environments like Cursor IDE and Replit.

📦 Installation

Installation Guide

1. Clone the repository:

   git clone https://github.com/PV-Bhat/gemsuite-mcp.git
   

2. Navigate to the directory:

   cd gemsuite-mcp
   

3. Install dependencies:

   npm install
   

4. Start the server:

   node index.js
   

💻 Usage Examples

Basic Usage

// Create a Gemini instance
const gem = new GemSuiteMCP();

// Perform a search task
gem.search('Gemini search example', (err, result) => {
  if (err) throw err;
  console.log(result);
});

Advanced Usage

// Custom model selection
gem.process({
  file_path: '/path/to/document.pdf',
  operation: 'analyze',
  model_id: 'models/gemini-2.0-flash-thinking'
}, (err, result) => {
  if (err) throw err;
  console.log(result);
});

📚 Documentation

• Official Documentation: GemSuite-MCP Documentation
• GitHub Repository: GemSuite-MCP Project
• Online Demo: Smithery.ai Demo

🤝 Contribution Guidelines

Contributions are welcome! To contribute:

1. Fork the repository:

   git fork https://github.com/PV-Bhat/gemsuite-mcp.git
   

2. Create a feature branch:

   git checkout -b feature/my-new-feature
   

3. Develop the feature.
4. Run tests:

   npm test
   

5. Commit changes:

   git commit -m 'Add my new feature'
   

6. Push to the branch:

   git push origin feature/my-new-feature
   

7. Submit a pull request.

For significant changes, please discuss them in the issue tracker first.

📄 License

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

🙏 Acknowledgments

Thanks to the following projects for their contributions:

• Lorhlona/geminiserchMCP: The original project that inspired this one.
• Model Context Protocol: Used for developing the MCP standard.
• Google Gemini: Provides powerful AI model support.

🔗 Links

• GitHub Repository
• Smithery.ai
• Mcp.so
• Glama
• Issue Tracker
• Model Context Protocol

_{Developed with ❤️ by [PV-Bhat](https://github.com/PV-Bhat)}