GemSuite-MCP
remote-capable server
The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.
Integrations
Integrates with Google Search to provide grounded responses to factual questions and current information.
Provides intelligent model selection between Gemini 2.0 Flash, Flash-Lite, and Flash Thinking models for different tasks, with file handling and multimodal capabilities.
Enables code generation and analysis directly within the Replit development environment using Gemini's capabilities.
GemSuite MCP
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 MCP is the ultimate Gemini API 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:
- Intelligence: Automatically selects the optimal Gemini model based on task and content
- Efficiency: Optimizes token usage and performance across different workloads
- Simplicity: Provides a clean, consistent API for complex AI operations
- Versatility: 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.
🚀 Installation
Option 1: Smithery.ai (Recommended)
Option 2: Manual Installation
🔑 API Key Setup
- Obtain a Gemini API key from Google AI Studio
- Set it as an environment variable:or create aCopy
.env
file in the project root:Copy
💎 Key Features
Unified File Handling
- Seamless File Processing: All tools support file inputs via the
file_path
parameter - Automatic Format Detection: Correct handling of various file types with appropriate MIME types
- Multimodal Support: Process images, documents, code files, and more
- Batch Processing: Support for processing multiple files in a single operation
Intelligent Model Selection
GemSuite MCP automatically selects the most appropriate Gemini model based on:
- Task Type: Search, reasoning, processing, or analysis
- Content Type: Text, code, images, or documents
- Complexity: Simple queries vs. complex reasoning
- User Preferences: Optional manual overrides
This intelligence ensures optimal performance while minimizing token usage.
Specialized Tools
Tool | Purpose | Model | Use Cases |
---|---|---|---|
gem_search | Information retrieval with search integration | Gemini Flash | Factual questions, current information, grounded responses |
gem_reason | Complex reasoning with step-by-step analysis | Gemini Flash Thinking | Math, science, coding problems, logical analysis |
gem_process | Fast, efficient content processing | Gemini Flash-Lite | Summarization, extraction, high-volume operations |
gem_analyze | Intelligent file analysis with auto-model selection | Auto-selected | Document analysis, code review, image understanding |
Robust Error Handling
- Exponential Backoff: Graceful handling of API rate limits
- Comprehensive Error Detection: Clear identification of error sources
- Actionable Messages: Detailed error information for troubleshooting
- Recovery Mechanisms: Intelligent fallbacks when primary approaches fail
🖥️ Usage
In Claude or Other MCP-Compatible Hosts
When using GemSuite MCP with Claude or other MCP-compatible hosts, the tools will be available directly in the assistant's toolkit. Simply call the appropriate tool for your needs:
Tool Selection Guide
gem_search
: For factual questions requiring search integrationgem_reason
: For complex problems requiring step-by-step reasoninggem_process
: For efficient processing of text or files (most token-efficient)gem_analyze
: For detailed analysis of files with automatic model selection
📚 Usage Examples
Claude Desktop Using GemSuite Gemini Search to access Google Search
Processing Files (Most Token-Efficient)
Analyzing Files
Complex Reasoning
Searching with Files
🧠 Model Characteristics
GemSuite MCP leverages three primary Gemini models, intelligently selecting the optimal model for each task:
Gemini 2.0 Flash
- 1M token context window: Process extensive content
- Search integration: Ground responses in current information
- Multimodal capabilities: Handle text, images, and more
- Balanced performance: Good mix of quality and speed
Gemini 2.0 Flash-Lite
- Most cost-efficient: Minimize token usage
- Fastest response times: Ideal for high-volume operations
- Text-focused: Optimized for text processing
- Optimal for efficiency: When search and reasoning aren't needed
Gemini 2.0 Flash Thinking
- Enhanced reasoning: Logical analysis and problem-solving
- Step-by-step analysis: Shows reasoning process
- Specialized capabilities: Excels at complex calculations
- Best for depth: When thorough analysis is necessary
🔄 Workflow Examples
Document Analysis Workflow
Code Review Workflow
🧩 Integration with Other MCP Hosts
GemSuite MCP works with any MCP-compatible host:
- Claude Desktop: Seamless integration with Claude's powerful reasoning capabilities
- Cursor IDE: Enhanced coding assistance with Gemini's capabilities
- Replit: Code generation and analysis directly in your development environment
- Other MCP Hosts: Compatible with any platform implementing the MCP standard
🛠️ Advanced Configuration
Custom Model Selection
You can override the automatic model selection by specifying the model_id
parameter:
Available Operations for gem_process
summarize
: Create a concise summaryextract
: Extract specific informationrestructure
: Reorganize content into a more useful formatsimplify
: Make complex content easier to understandexpand
: Add detail or context to contentcritique
: Provide critical analysisfeedback
: Offer constructive feedbackanalyze
: General analysis of content
🔧 Contributing
Contributions are welcome! Here's how to get started:
- Fork the repository
- Create a feature branch:
git checkout -b feature/my-new-feature
- Make your changes
- Run tests:
npm test
- Commit your changes:
git commit -m 'Add my new feature'
- Push to your branch:
git push origin feature/my-new-feature
- Submit a pull request
For major changes, please open an issue first to discuss what you'd like to change.
📜 License
This project is licensed under the MIT License - see the LICENSE file for details.
🙏 Acknowledgements
- Lorhlona/geminiserchMCP - The original project that inspired this enhanced version
- Model Context Protocol - For developing the MCP standard
- Google Gemini - For the powerful AI models that power this server
🔗 Links
This server cannot be installed
The ultimate Gemini API interface for MCP hosts, intelligently selecting models for the task at hand—delivering optimal performance, minimal token cost, and seamless integration.