GemSuite is a comprehensive integration layer for Google's Gemini API within MCP-compatible hosts. It automatically selects the optimal Gemini model based on task requirements to balance performance and token efficiency. Key features include: - Intelligent model selection that matches workload complexity to the appropriate Gemini model - Advanced file handling with automatic format detection for multiple file types - Token cost optimization across different operations - Seamless integration with Claude, Cursor, Replit, and other MCP-compatible environments - Unified API for document analysis, complex problem solving, and information retrieval tasks

GemSuite MCP: The Most Comprehensive Gemini API Integration for Model Context Protocol

[](https://opensource.org/licenses/MIT) [](https://www.typescriptlang.org/) [](https://modelcontextprotocol.ai/) [](https://smithery.ai/server/@PV-Bhat/gemsuite-mcp) [](https://nodejs.org/)

Professional Gemini API integration for Claude and all MCP-compatible hosts with intelligent model selection and advanced file handling

*Evolved from the geminiserchMCP project with enhanced capabilities*

Installation • Features • Usage • Examples • Models • Contributing

🌟 What is GemSuite MCP?

GemSuite (Model Context Protoco) MCP is the ultimate Gemini API integration interface for MCP hosts, intelligently selecting models for the task at hand—delivering optimal performance, minimal token cost, and seamless integration. It enables any MCP-compatible host (Claude, Cursor, Replit, etc.) to seamlessly leverage Gemini's capabilities with a focus on:

1. Intelligence: Automatically selects the optimal Gemini model based on task and content 2. Efficiency: Optimizes token usage and performance across different workloads 3. Simplicity: Provides a clean, consistent API for complex AI operations 4. Versatility: Advanced file handling; Handles multiple file types, operations, and use cases

Whether you're analyzing documents, solving complex problems, processing large text files, or searching for information, GemSuite MCP provides the right tools with the right models for the job.

Why GemSuite MCP?

Unlike other Gemini MCP servers that offer limited functionality, GemSuite MCP provides:

✅ Intelligent Model Selection: Automatically selects the optimal Gemini model based on task ✅ Unified File Handling: Seamlessly processes various file types with automatic format detection ✅ Comprehensive Tool Suite: Four specialized tools covering search, reasoning, processing, and analysis ✅ Production-Ready: Deployed and validated on Smithery.ai, MCP.so, and Glama.io

🚀 Installation

Option 1: Smithery.ai (Recommended)

# Install directly via Smithery CLI
npx -y @smithery/cli@latest install @PV-Bhat/gemsuite-mcp --client claude

Option 2: Manual Installation

# Clone the repository
git clone https://github.com/PV-Bhat/gemsuite-mcp.git
cd gemsuite-mcp
Install dependencies
npm install
Set your Gemini API key
echo "GEMINI_API_KEY=your_api_key_here" > .env
Build the project
npm run build
Start the server
npm start

🔑 API Key Setup

1. Obtain a Gemini API key from Google AI Studio 2. Set it as an environment variable:

   export GEMINI_API_KEY=your_api_key_here
   

   GEMINI_API_KEY=your_api_key_here
   

💎 Key Features

Unified File Handling

Intelligent Model Selection

GemSuite MCP automatically selects the most appropriate Gemini model based on:

This intelligence ensures optimal performance while minimizing token usage.

```mermaid graph TD A[Task Request] --> B{Task Type} B -->|Search| C[Gemini Flash] B -->|Reasoning| D[Gemini Flash Thinking] B -->|Processing| E[Gemini Flash-Lite] B -->|Analysis| F{Fi