What is an MCP Server?

An MCP (Model Context Protocol) server acts as a bridge, allowing AI models to access and interact with external data sources and tools. It standardizes how applications provide context to LLMs.

What is the Gemini Imagen 3.0 MCP Server?

The Gemini Imagen 3.0 MCP Server is a professional Model Context Protocol (MCP) server implementation that harnesses Google’s Imagen 3.0 model through the Gemini API for high-quality image generation.

What are the prerequisites for using this server?

You need Node.js 18 or higher, a Google Gemini API key, and Claude Desktop or another MCP-compatible host.

How do I install the Gemini Imagen 3.0 MCP Server?

1. Clone the repository.
2. Install dependencies using npm install.
3. Build the TypeScript code using npm run build.
4. Configure Claude Desktop by adding the server configuration to claude_desktop_config.json.

Where are the generated images saved?

Images are automatically saved in G:image-gen3-google-mcp-serverimages by default.

What naming convention is used for the generated images?

Filenames follow the pattern: {sanitized-prompt}-{timestamp}-{index}.png.

What is the generate_images tool?

This tool generates images using Google’s Imagen 3.0 model. It requires a text prompt and an optional number of images (1-4).

What is the create_image_html tool?

This tool creates HTML preview tags for generated images, allowing you to view them locally in a web browser. It requires an array of image file paths.

What error codes does the server implement?

The server implements tool_not_found (1) when the requested tool is not available and execution_error (2) when image generation or HTML creation fails.

How does this server integrate with UBOS?

Integrating with UBOS allows you to orchestrate image generation workflows, connect to enterprise data, build custom AI Agents, and manage multi-agent systems for collaborative image generation and complex visual tasks.