Gemini MCP: Custom Image Generation & Seamless Scaling

Unleash Gemini’s AI magic with this MCP server—generate stunning, custom images fast, seamlessly scaling for creative pros who demand quality without the coding chaos." )

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About Gemini MCP

What is Gemini MCP: Custom Image Generation & Seamless Scaling?

Gemini MCP is a specialized server framework leveraging Google’s Gemini 2 API to enable on-demand image synthesis with granular control. It’s built on the Model Context Protocol (MCP), designed to let developers quickly spin up scalable image generation pipelines while maintaining fine-tuned parameters like aspect ratios and content restrictions. Think of it as your bridge between creative vision and production-ready AI art.

How to use Gemini MCP: Custom Image Generation & Seamless Scaling?

First, install dependencies using npm. Set up your Google API key in a .env file—this is your gateway to Gemini 2’s experimental features. Once configured, kick off the server and use the MCP inspector tool for quick validation. The real magic happens through structured JSON requests specifying prompts like “neon-lit cyberpunk cityscape” alongside optional parameters for output quantity and formatting.

Gemini MCP Features

Key Features of Gemini MCP: Custom Image Generation & Seamless Scaling?

Aspect Ratio Mastery: Choose from 1:1, 9:16, or 3:4 compositions to match your platform’s requirements
Content Control: Adjust adult content generation settings with the personGeneration flag to comply with platform policies
Batch Processing: Generate 1-10 images per request, perfect for A/B testing visuals without iterative prompting
Scalability Built-In: MCP’s modular design lets you easily expand to handle fluctuating demand

Use cases of Gemini MCP: Custom Image Generation & Seamless Scaling?

Gemini MCP FAQ

FAQ from Gemini MCP: Custom Image Generation & Seamless Scaling?

Q: Can I use this for commercial projects?
A: Yes, but ensure your Google Cloud billing account has enabled the Vision API and adheres to content policies.

Q: How many images can I generate per minute?
A: The API’s quota system applies, but MCP’s async handling optimizes throughput for burst workflows.

Q: What if my prompt returns unexpected results?
A: Refine with specificity—add terms like “minimalist” or “detailed” to guide the model’s output style.

Content

Gemini MCP Image Generation Server

This is a Model Context Protocol (MCP) server that provides image generation capabilities using Google's Gemini 2 API.

Setup

Install dependencies:

npm install

Set up your environment variables: Create a .env file in the root directory and add your Google API key:

GEMINI_API_KEY=your_api_key_here

Usage

Run the server:

npm start

To test

npx @modelcontextprotocol/inspector npm run start

Available Tools

generateImage

Generates images using Gemini 2's experimental image generation API.

Parameters:

prompt (string, required): The description of the image you want to generate
numSamples (number, optional, default: 4): Number of images to generate
aspectRatio (string, optional, default: '1:1'): Aspect ratio of the generated images
personGeneration (string, optional, default: 'ALLOW_ADULT'): Person generation settings

Example MCP request:

{
  "tool": "generateImage",
  "params": {
    "prompt": "A serene mountain landscape at sunset",
    "numSamples": 2,
    "aspectRatio": "16:9"
  }
}

Notes

This server uses the experimental image generation feature of Gemini 2
Make sure you have appropriate access and API keys from Google
The server communicates using the Model Context Protocol over stdio