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Gemini MCP Image Generation Server

by sanxfxteam
import { GoogleGenerativeAI } from "@google/generative-ai"; import fs from "fs"; import dotenv from 'dotenv'; // Load environment variables from .env file dotenv.config(); const genAI = new GoogleGenerativeAI(process.env.GEMINI_API_KEY); async function generateImage() { const contents = "Hi, can you create a 3d rendered image of a pig " + "with wings and a top hat flying over a happy " + "futuristic scifi city with lots of greenery?"; // Set responseModalities to include "Image" so the model can generate an image const model = genAI.getGenerativeModel({ model: "gemini-2.0-flash-exp-image-generation", generationConfig: { responseModalities: ['Text', 'Image'] }, }); try { const response = await model.generateContent(contents); for (const part of response.response.candidates[0].content.parts) { // Based on the part type, either show the text or save the image if (part.text) { console.log(part.text); } else if (part.inlineData) { const imageData = part.inlineData.data; const buffer = Buffer.from(imageData, 'base64'); fs.writeFileSync('gemini-native-image.png', buffer); console.log('Image saved as gemini-native-image.png'); } } } catch (error) { console.error("Error generating content:", error); } } generateImage();

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