Gemini Image Generator MCP Server
by MCP-Mirror
This MCP server allows AI assistants to generate high-quality images from text prompts using Google's Gemini model. It handles prompt engineering, text-to-image conversion, and local image storage.
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What is Gemini Image Generator MCP Server?
This is an MCP server that enables AI assistants to generate images using Google's Gemini AI model. It manages the entire process, from prompt engineering to storing the generated images locally.
How to use Gemini Image Generator MCP Server?
Install the server, configure it with your Gemini API key and output path, and then use an MCP client (like Claude Desktop) to send text prompts to the server. The server will generate the image and return the image data and file path.
Key features of Gemini Image Generator MCP Server
Text-to-image generation using Gemini 2.0 Flash
Image-to-image transformation based on text prompts
Automatic intelligent filename generation based on prompts
Automatic translation of non-English prompts
Local image storage with configurable output path
Use cases of Gemini Image Generator MCP Server
Generating images from text descriptions
Transforming existing images based on text prompts
Creating visual content for AI assistants
Automating image creation workflows
FAQ from Gemini Image Generator MCP Server
What is an MCP server?
What is an MCP server?
MCP stands for Message Communication Protocol. It allows different AI tools to communicate with each other.
What is Gemini?
What is Gemini?
Gemini is Google's family of multimodal AI models.
Do I need a Google AI API key to use this server?
Do I need a Google AI API key to use this server?
Yes, you need a Google AI API key to access the Gemini model.
What MCP clients are compatible with this server?
What MCP clients are compatible with this server?
This server is compatible with any MCP-compatible client, such as Claude Desktop, Cursor, or FastMCP.
Where are the generated images stored?
Where are the generated images stored?
The generated images are stored locally in the output path you configure in the .env file.