GemForge (Gemini Tools)

Overview

GemForge-Gemini-Tools-MCP: Enterprise-grade Gemini integration for your favorite MCP agents. Supercharge Claude, Roo Code, and Windsurf with codebase analysis, live search, text/PDF/image processing, and more.

Quick Navigation

• Features
• Quick Start
• Configuration
• Tools
• Heavy-Duty Reliability
• Deployment
• Examples
• Community
• Documentation

Why GemForge?

GemForge is the essential bridge between Google's Gemini AI and the MCP ecosystem:

• Real-Time Web Access: Fetch breaking news, market trends, and current data with gemini_search

• Advanced Reasoning: Process complex logic problems with step-by-step thinking via gemini_reason

• Code Mastery: Analyze full repositories, generate solutions, and debug code with gemini_code

• Multi-File Processing: Handle 60+ file formats including PDFs, images, and more with gemini_fileops

• Intelligent Model Selection: Automatically routes to optimal Gemini model for each task

• Enterprise-Ready: Robust error handling, rate limit management, and API fallback mechanisms

Quick Start

One-Line Install

npx @gemforge/mcp-server@latest init

Manual Setup

1. Create configuration file (claude_desktop_config.json):

{
  "mcpServers": {
    "GemForge": {
      "command": "node",
      "args": ["./dist/index.js"],
      "env": {
        "GEMINI_API_KEY": "your_api_key_here"
      }
    }
  }
}

2. Install and run:

npm install gemforge-mcp
npm start

Watch 30-second setup demo →

Heavy-Duty Reliability

GemForge is built for production environments:

• Support for 60+ File Types: Process everything from code to documents to images
• Automatic Model Fallbacks: Continues functioning even during rate limits or service disruptions
• Enterprise-Grade Error Logging: Detailed diagnostics for troubleshooting
• API Resilience: Exponential backoff, retry logic, and seamless model switching
• Full Repository Support: Analyze entire codebases with configurable inclusion/exclusion patterns
• XML Content Processing: Specialized handling for structured data

Key Tools

{
  "toolName": "gemini_search",
  "toolParams": {
    "query": "Latest advancements in quantum computing",
    "enable_thinking": true
  }
}

{
  "toolName": "gemini_code",
  "toolParams": {
    "question": "Identify improvements and new features",
    "directory_path": "path/to/project",
    "repomix_options": "--include \"**/*.js\" --no-gitignore"
  }
}

{
  "toolName": "gemini_fileops",
  "toolParams": {
    "file_path": ["contract_v1.pdf", "contract_v2.pdf"],
    "operation": "analyze",
    "instruction": "Compare these contract versions and extract all significant changes."
  }
}

Configuration

GemForge offers flexible configuration options:

GEMINI_API_KEY=your_api_key_here       # Required: Gemini API key
GEMINI_PAID_TIER=true                  # Optional: Set to true if using paid tier (better rate limits)
DEFAULT_MODEL_ID=gemini-2.5-pro        # Optional: Override default model selection
LOG_LEVEL=info                         # Optional: Set logging verbosity (debug, info, warn, error)

{
  "mcpServers": {
    "GemForge": {
      "command": "node",
      "args": ["./dist/index.js"],
      "env": {
        "GEMINI_API_KEY": "your_api_key_here"
      }
    }
  }
}

Deployment

Smithery.ai

One-click deployment via Smithery.ai

Docker

docker run -e GEMINI_API_KEY=your_api_key ghcr.io/pv-bhat/gemforge:latest

Self-Hosted

Use our MCP.so Directory listing for integration instructions.

What Sets GemForge Apart?

• Cross-Ecosystem Power: Bridge Google's AI with Claude and other MCP agents
• Multi-File Analysis: Compare documents, images, or code versions
• Smart Routing: Automatic model selection based on task requirements
• Production-Ready: Built for enterprise environments

Community & Support

• Join Us: MCP Discord | GemForge Discord
• Contribute: GitHub Discussions
• Feedback: Open an issue or share thoughts on Discord

Documentation

Visit our Documentation Site for:

• Advanced usage tutorials
• API reference
• Troubleshooting tips

License

Licensed under the MIT License. See LICENSE for details.

Acknowledgments

• Google Gemini API for providing the underlying AI capabilities
• Model Context Protocol (MCP) for standardizing AI tool interfaces