npm-mcp-packages-comparison

Purpose

Comprehensive comparison of npm packages and Model Context Protocol (MCP) servers for AI image generation across multiple providers (OpenAI, Google, Stability AI, Midjourney alternatives).

Executive Summary

2025 Landscape:

• OpenAI DALL-E models deprecating - DALL-E 2 & 3 will be sunset on May 12, 2026
• GPT Image models are the new OpenAI standard (gpt-image-1.5, gpt-image-1, gpt-image-1-mini)
• MCP adoption accelerating - OpenAI officially adopted MCP in March 2025
• Multi-provider packages increasingly important as vendor landscape fragments
• Google Nano Banana offers best free tier (500 requests/day)

NPM Packages Overview

Multi-Provider Packages (Recommended)

1. ai-image

Package: npm install ai-image

Description: Unified wrapper for image generation APIs with CLI support

Features:

• ✅ Supports OpenAI GPT Image and Replicate
• ✅ Easy-to-use CLI with npx support
• ✅ Programmatic API for integration
• ✅ Custom size, quality settings
• ✅ Multiple model support (DALL-E 2/3)
• ✅ Provider selection via -p, --provider <provider> flag

Best For: Projects needing both OpenAI and Replicate with simple CLI access

CLI Usage:

npx ai-image "a futuristic city" -p openai
npx ai-image "abstract art" -p replicate

Programmatic Usage:

const { generateImage } = require('ai-image');
const image = await generateImage('a futuristic city', { provider: 'openai' });

2. Vercel AI SDK (ai)

Package: npm install ai @ai-sdk/openai @ai-sdk/anthropic @ai-sdk/google

Description: Unified API for multiple LLM providers with image generation support

Features:

• ✅ Unified API across OpenAI, Anthropic, Google, and more
• ✅ Image generation via agents (ImageGenerationAgentMessage)
• ✅ React components for UI (ImageGenerationView)
• ✅ Streaming support
• ✅ Production-ready with enterprise features
• ✅ Vercel AI Gateway integration

Best For: Full-stack applications using Vercel ecosystem, React-based UIs

Example:

import { createOpenAI } from '@ai-sdk/openai';
import { generateImage } from 'ai';

const openai = createOpenAI({ apiKey: process.env.OPENAI_API_KEY });
const result = await generateImage({
  model: openai.image('gpt-image-1.5'),
  prompt: 'a serene landscape',
});

3. Imagine.js (@themaximalist/imagine.js)

Package: npm install @themaximalist/imagine.js

Description: Multi-provider image generation with easy provider switching

Features:

• ✅ Prevents vendor lock-in with easy provider switching
• ✅ Supports a111 (local AUTOMATIC1111), stability, replicate
• ✅ Integrates with LLM.js for prompt enhancement
• ✅ Simple API design
• ✅ Remix and quality-boost prompts automatically

Best For: Developers wanting maximum flexibility and local inference options

Example:

const Imagine = require('@themaximalist/imagine.js');
const imagine = new Imagine({ provider: 'stability' });
const image = await imagine.generate('cyberpunk cityscape');

OpenAI-Specific Packages

4. openai (Official)

Package: npm install openai

Description: Official OpenAI SDK with image generation, editing, and variations

Features:

• ✅ Official support from OpenAI
• ✅ GPT Image models (gpt-image-1.5, gpt-image-1, gpt-image-1-mini)
• ✅ Legacy DALL-E 2 & 3 support (until May 2026)
• ✅ Image generation from scratch
• ✅ Image editing with prompts
• ✅ Variations (DALL-E 2 only)
• ✅ TypeScript support

Important: DALL-E 2 and DALL-E 3 are deprecated and will stop working on May 12, 2026. Use GPT Image models instead.

Example:

import OpenAI from 'openai';
const openai = new OpenAI({ apiKey: process.env.OPENAI_API_KEY });

// Generate with GPT Image (new)
const response = await openai.images.generate({
  model: 'gpt-image-1.5',
  prompt: 'a white siamese cat',
  n: 1,
  size: '1024x1024',
});

// Edit existing image
const edit = await openai.images.edit({
  model: 'gpt-image-1',
  image: fs.createReadStream('input.png'),
  prompt: 'add sunglasses to the cat',
});

// Create variations (DALL-E 2 only)
const variations = await openai.images.createVariation({
  model: 'dall-e-2',
  image: fs.createReadStream('input.png'),
  n: 2,
});

Pricing: No free tier - usage-based pricing on OpenAI account

5. dalle-node

Package: npm install dalle-node

Description: DALL-E wrapper returning arrays of image generations

Features:

• ✅ Simple prompt-to-image interface
• ✅ Returns array of generations
• ❌ Outdated (last updated 2+ years ago)

Status: ⚠️ Consider using official openai package instead

6. node-dalle2

Package: npm install node-dalle2

Description: Type-safe DALL-E 2 library

Features:

• ✅ Type-safe TypeScript support
• ✅ DALL-E 2 API wrapper
• ❌ Not healthy version release cadence (last release 1+ year ago)
• ❌ DALL-E 2 is deprecated

Status: ⚠️ Deprecated - use official openai package

Google Gemini Packages

7. @google/generative-ai (Nano Banana)

Package: npm install @google/generative-ai

Description: Official Google Generative AI SDK with Nano Banana image generation

Features:

• ✅ Official Google support
• ✅ Gemini 2.5 Flash Image (Nano Banana) - 500 free requests/day
• ✅ Gemini 3 Pro Image (Nano Banana Pro) - premium quality
• ✅ Text-to-image, image-to-image, multi-image composition
• ✅ High-fidelity text rendering (logos, diagrams)
• ✅ Up to 4K output resolution

Best For: Projects needing free tier or excellent text rendering in images

Example:

import { GoogleGenerativeAI } from '@google/generative-ai';

const genAI = new GoogleGenerativeAI(process.env.GEMINI_API_KEY);
const model = genAI.getGenerativeModel({ model: 'gemini-2.5-flash-image' });

const result = await model.generateContent([
  'A futuristic cityscape at sunset with flying cars'
]);

const image = result.response.images[0];

Pricing:

• Free: 500 requests/day (Gemini 2.5 Flash Image)
• Paid: ~$0.15 per 4K generation

Stable Diffusion Packages

8. stable-diffusion-api

Package: npm install stable-diffusion-api

Description: TypeScript client for AUTOMATIC1111/stable-diffusion-webui API

Features:

• ✅ Connects to local Stable Diffusion WebUI
• ✅ Full API method coverage
• ✅ ControlNet extension support
• ❌ Requires running webui with --api flag
• ❌ Last updated 2 years ago (v0.0.7)

Best For: Projects using self-hosted AUTOMATIC1111 webui

Setup:

# Start webui with API enabled
./webui.sh --api

Example:

import StableDiffusionApi from 'stable-diffusion-api';

const api = new StableDiffusionApi({
  host: 'localhost',
  port: 7860,
  protocol: 'http',
});

const result = await api.txt2img({
  prompt: 'a beautiful landscape',
  steps: 20,
  sampler_name: 'Euler a',
});

9. stable-diffusion-nodejs

Package: npm install stable-diffusion-nodejs

Description: GPU-accelerated JavaScript runtime for Stable Diffusion using ONNX

Features:

• ✅ Local GPU acceleration (CUDA, DirectML)
• ✅ ONNX runtime for cross-platform support
• ✅ No external dependencies once models downloaded
• ✅ Full pipeline control
• ❌ Requires GPU with CUDA or DirectML

Best For: Local inference with GPU acceleration, privacy-sensitive applications

Example:

import { StableDiffusionPipeline } from 'stable-diffusion-nodejs';

const pipeline = await StableDiffusionPipeline.fromPretrained(
  'path/to/model',
  { provider: 'cuda' } // or 'directml' on Windows, 'cpu' on macOS
);

const image = await pipeline.generateImage('cyberpunk city');

10. stable-diffusion-rest-api

Package: npm install stable-diffusion-rest-api

Description: Local Stable Diffusion REST API for M1/M2 MacBooks

Features:

• ✅ Optimized for Apple Silicon (M1/M2)
• ✅ REST API server
• ✅ Command-line options (—port, —cors, —concurrency)
• ❌ Last published 3 years ago
• ❌ Requires Python v3.10 and Node.js v16

Status: ⚠️ Outdated - consider alternatives

Specialized Packages

11. @imgly/plugin-ai-image-generation-web

Package: npm install @imgly/plugin-ai-image-generation-web

Description: CreativeEditor SDK plugin for AI image generation via fal.ai

Features:

• ✅ Integrates with CreativeEditor SDK
• ✅ Multiple providers via fal.ai:
  • FalAiImage.RecraftV3
  • FalAiImage.NanoBanana
  • FalAiImage.Recraft20b
  • OpenAiImage.GptImage1
• ✅ Text-to-image and image-to-image transformations
• ✅ In-editor image generation workflow

Best For: Applications already using CreativeEditor SDK

12. @runpod/ai-sdk-provider

Package: npm install @runpod/ai-sdk-provider

Description: RunPod provider for Vercel AI SDK

Features:

• ✅ Integrates with Vercel AI SDK ecosystem
• ✅ Access to RunPod’s public endpoints
• ✅ Language models + image generation
• ✅ Recently updated (v1.0.1)

Best For: Projects using RunPod infrastructure + Vercel AI SDK

Model Context Protocol (MCP) Servers

What is MCP?

The Model Context Protocol (MCP) is an open standard introduced by Anthropic in November 2024 to standardize how AI systems integrate with external tools and data sources.

Key Events:

• Nov 2024: Anthropic releases MCP as open standard
• Mar 2025: OpenAI officially adopts MCP across products
• Dec 2025: MCP donated to Agentic AI Foundation (Linux Foundation)

MCP Image Generation Servers

1. mcp-image-gen (sarthakkimtani)

GitHub: sarthakkimtani/mcp-image-gen

Description: MCP server enabling image generation via Together AI

Features:

• ✅ Powered by Flux.1 Schnell model
• ✅ Customizable dimensions
• ✅ High-quality image generation
• ✅ Standardized MCP interface
• ✅ Together AI backend

Setup:

{
  "mcpServers": {
    "image-gen": {
      "command": "npx",
      "args": ["-y", "mcp-image-gen"],
      "env": {
        "TOGETHER_API_KEY": "your-api-key"
      }
    }
  }
}

Best For: Claude Code users wanting Together AI image generation

2. gmkr-mcp-imagegen

MCP Server: gmkr-mcp-imagegen (on LobeHub)

Description: Multi-provider MCP server for Replicate and Together AI

Features:

• ✅ Supports Replicate and Together AI
• ✅ Provider switching via environment variables
• ✅ Standardized tool interface
• ❌ Requires provider-specific API tokens

Configuration:

{
  "mcpServers": {
    "gmkr-image": {
      "command": "npx",
      "args": ["-y", "gmkr-mcp-imagegen"],
      "env": {
        "PROVIDER": "replicate",
        "REPLICATE_API_TOKEN": "your-token"
      }
    }
  }
}

Provider Options:

• PROVIDER=replicate → Requires REPLICATE_API_TOKEN
• PROVIDER=together → Requires TOGETHER_API_KEY

3. imagegen-mcp (OpenAI Wrapper)

GitHub: spartanz51/imagegen-mcp

Description: MCP server wrapping OpenAI’s Image Generation & Editing APIs

Features:

• ✅ Text-to-image generation
• ✅ Image-to-image editing with masks
• ✅ No extra plugins required
• ✅ Direct OpenAI API integration

Setup:

{
  "mcpServers": {
    "openai-images": {
      "command": "npx",
      "args": ["-y", "imagegen-mcp"],
      "env": {
        "OPENAI_API_KEY": "your-api-key"
      }
    }
  }
}

Best For: Claude Code users wanting OpenAI image generation via MCP

OpenAI Responses API with MCP

Announcement: March 2025

OpenAI’s Responses API now supports:

• ✅ Remote MCP server connections
• ✅ Image generation as a tool
• ✅ Streaming image previews during generation
• ✅ Multi-turn image editing workflows

Example:

import OpenAI from 'openai';
const openai = new OpenAI();

const response = await openai.responses.create({
  model: 'gpt-4',
  tools: [{
    type: 'mcp_server',
    mcp_server: {
      url: 'https://your-mcp-server.com'
    }
  }],
  messages: [
    { role: 'user', content: 'Generate an image of a sunset' }
  ]
});

Provider Comparison

Feature Matrix

Quality & Use Case Comparison

Midjourney API Alternatives

The Midjourney Challenge

Problem: Midjourney has no official API and remains Discord-only in 2025.

Risks of unofficial APIs:

• Account bans
• Discord rate limits
• Queue delays
• Service instability

Third-Party Midjourney API Services

⚠️ Warning: All unofficial Midjourney APIs risk account bans and service disruption.

Official Midjourney Alternatives

Instead of unofficial Midjourney APIs, consider these official alternatives:

1. Flux (by Black Forest Labs)

• ✅ Official API available
• ✅ “Midjourney feel” with API access
• ✅ Great at prompt following
• ✅ Low-latency generation
• ✅ In-context generation support

Recommended: Best Midjourney alternative with official API support.

2. Leonardo AI

• ✅ Clean web interface
• ✅ Strong artistic quality
• ✅ Real-time editing tools
• ✅ Generous free tier

Best For: All-around Midjourney alternative with great UX

3. Adobe Firefly

• ✅ Trained on licensed content
• ✅ Safe for commercial use
• ✅ Enterprise-friendly

Best For: Business/commercial applications

4. Stable Diffusion 3

• ✅ 8.1 billion parameters (April 2024 release)
• ✅ Open source
• ✅ Local inference possible
• ✅ API via Stability AI

Best For: Developers wanting open source with strong quality

Recommendations by Use Case

1. Rapid Prototyping / High Volume

Best Choice: Google Nano Banana

Package: @google/generative-ai

Why:

• 500 free requests/day
• Fast generation
• Good quality for prototypes
• Official Google support

2. Multi-Provider Flexibility

Best Choice: Vercel AI SDK or Imagine.js

Packages:

• ai + @ai-sdk/openai + @ai-sdk/google
• @themaximalist/imagine.js

Why:

• Avoid vendor lock-in
• Switch providers easily
• Unified API across models
• Production-ready tooling

3. Claude Code / MCP Integration

Best Choice: MCP Image Generation Servers

Servers:

• mcp-image-gen (Together AI / Flux)
• imagegen-mcp (OpenAI GPT Image)

Why:

• Native Claude Code integration
• Standardized tool interface
• Easy configuration

4. Highest Quality (Official API)

Best Choice: Flux by Black Forest Labs

Alternative: Google Nano Banana Pro

Why:

• Midjourney-level quality
• Official API support
• Reliable service
• Production-ready

5. Local Inference / Privacy

Best Choice: Stable Diffusion

Packages:

• stable-diffusion-nodejs (GPU-accelerated)
• stable-diffusion-api (AUTOMATIC1111 webui)

Why:

• 100% local, no API calls
• Open source
• No usage costs
• Full control

6. ChatGPT Integration

Best Choice: OpenAI GPT Image

Package: openai

Why:

• Direct ChatGPT Plus integration
• Precise prompt following
• Official OpenAI support
• High quality results

7. Text Rendering (Logos, Diagrams)

Best Choice: Google Nano Banana Pro

Package: @google/generative-ai

Why:

• Excellent text rendering
• High-fidelity output
• Specialized for diagrams/posters
• Reliable text placement

8. Cost-Conscious Production

Best Choice: Google Nano Banana (free tier) → GPT Image (paid)

Strategy:

• Use free tier for development/testing
• Switch to paid tier for production
• Monitor usage to stay in free tier when possible

Implementation Quick Start

Multi-Provider Setup (Recommended)

npm install ai @ai-sdk/openai @ai-sdk/google

import { createOpenAI } from '@ai-sdk/openai';
import { createGoogleGenerativeAI } from '@ai-sdk/google';
import { generateImage } from 'ai';

// Configure providers
const openai = createOpenAI({ apiKey: process.env.OPENAI_API_KEY });
const google = createGoogleGenerativeAI({ apiKey: process.env.GEMINI_API_KEY });

// Generate with OpenAI
const openaiImage = await generateImage({
  model: openai.image('gpt-image-1.5'),
  prompt: 'a serene landscape',
});

// Generate with Google (free tier!)
const googleImage = await generateImage({
  model: google.image('gemini-2.5-flash-image'),
  prompt: 'a serene landscape',
});

Simple Single-Provider Setup

npm install @google/generative-ai

import { GoogleGenerativeAI } from '@google/generative-ai';

const genAI = new GoogleGenerativeAI(process.env.GEMINI_API_KEY);
const model = genAI.getGenerativeModel({ model: 'gemini-2.5-flash-image' });

const result = await model.generateContent(['a futuristic cityscape']);
const image = result.response.images[0];

MCP Server Setup (Claude Code)

1. Install MCP server:

npx -y mcp-image-gen

2. Configure Claude Code (~/.claude/mcp.json):

{
  "mcpServers": {
    "image-gen": {
      "command": "npx",
      "args": ["-y", "mcp-image-gen"],
      "env": {
        "TOGETHER_API_KEY": "your-together-api-key"
      }
    }
  }
}

3. Use in Claude Code:

Generate an image of a futuristic cityscape at sunset

Claude Code will automatically use the MCP image generation tool.

Migration Guides

Migrating from DALL-E 2/3 to GPT Image

Deadline: May 12, 2026

Before (Deprecated):

const response = await openai.images.generate({
  model: 'dall-e-3',
  prompt: 'a white siamese cat',
});

After (Recommended):

const response = await openai.images.generate({
  model: 'gpt-image-1.5',
  prompt: 'a white siamese cat',
});

Changes:

• Replace dall-e-2 → gpt-image-1-mini or gpt-image-1
• Replace dall-e-3 → gpt-image-1.5 or gpt-image-1
• API interface remains the same

Adding MCP to Existing Image Generation

If you have:

// Existing image generation
const { generateImage } = require('ai-image');
const img = await generateImage('prompt', { provider: 'openai' });

Add MCP server for Claude Code access:

1. Install MCP server:

npm install -g mcp-image-gen

2. Configure ~/.claude/mcp.json:

{
  "mcpServers": {
    "image-gen": {
      "command": "mcp-image-gen",
      "env": {
        "TOGETHER_API_KEY": "your-key"
      }
    }
  }
}

3. Now both programmatic AND Claude Code access work!

Common Patterns

Pattern 1: Free Tier → Paid Fallback

async function generateWithFallback(prompt) {
  try {
    // Try free tier first (Google Nano Banana - 500/day)
    const genAI = new GoogleGenerativeAI(process.env.GEMINI_API_KEY);
    const model = genAI.getGenerativeModel({ model: 'gemini-2.5-flash-image' });
    const result = await model.generateContent([prompt]);
    return result.response.images[0];
  } catch (error) {
    if (error.message.includes('quota')) {
      // Fall back to paid OpenAI
      const openai = new OpenAI({ apiKey: process.env.OPENAI_API_KEY });
      const response = await openai.images.generate({
        model: 'gpt-image-1.5',
        prompt: prompt,
      });
      return response.data[0];
    }
    throw error;
  }
}

Pattern 2: Multi-Provider Quality Comparison

async function compareProviders(prompt) {
  const results = await Promise.all([
    generateWithOpenAI(prompt),
    generateWithGoogle(prompt),
    generateWithStableDiffusion(prompt),
  ]);

  return {
    openai: results[0],
    google: results[1],
    stableDiffusion: results[2],
  };
}

Pattern 3: Local → Cloud Fallback

async function generateWithLocalFallback(prompt) {
  if (hasLocalGPU()) {
    // Try local Stable Diffusion first
    const pipeline = await StableDiffusionPipeline.fromPretrained('model');
    return await pipeline.generateImage(prompt);
  }

  // Fallback to cloud API
  const genAI = new GoogleGenerativeAI(process.env.GEMINI_API_KEY);
  const model = genAI.getGenerativeModel({ model: 'gemini-2.5-flash-image' });
  const result = await model.generateContent([prompt]);
  return result.response.images[0];
}

Best Practices

1. API Key Management

✅ DO:

• Store keys in environment variables
• Use .env files (never commit to git)
• Rotate keys regularly
• Use different keys for dev/staging/prod

❌ DON’T:

• Hardcode API keys in source code
• Share keys in Slack/email
• Use production keys in development

2. Cost Optimization

✅ DO:

• Use free tiers for development (Google Nano Banana: 500/day)
• Cache generated images
• Implement rate limiting
• Monitor usage with alerts

❌ DON’T:

• Regenerate images unnecessarily
• Skip caching in production
• Leave unlimited generation endpoints public

3. Error Handling

✅ DO:

• Implement retry logic with exponential backoff
• Handle quota errors gracefully
• Provide fallback providers
• Log failures for debugging

❌ DON’T:

• Assume API calls always succeed
• Ignore rate limit errors
• Crash on provider failures

4. Provider Selection

For prototyping: Google Nano Banana (free tier)

For production:

• High quality: Flux, Nano Banana Pro
• Cost-effective: GPT Image 1-mini, Nano Banana
• Privacy-sensitive: Local Stable Diffusion
• ChatGPT users: GPT Image 1.5

Limitations & Considerations

OpenAI DALL-E / GPT Image

Limitations:

• ❌ No free tier
• ❌ DALL-E 2/3 deprecated (May 12, 2026)
• ❌ Rate limits apply
• ✅ High quality
• ✅ ChatGPT integration

Google Nano Banana

Limitations:

• ⚠️ 500 requests/day on free tier
• ❌ No free tier for Pro version
• ✅ Excellent text rendering
• ✅ Fast generation
• ✅ Up to 4K output

Stable Diffusion

Limitations:

• ⚠️ Requires GPU for good performance
• ⚠️ Model quality varies
• ⚠️ Outdated npm packages
• ✅ 100% local/private
• ✅ Open source
• ✅ No API costs

Midjourney

Limitations:

• ❌ No official API
• ❌ Discord-only interface
• ❌ Unofficial APIs risk account bans
• ✅ Highest quality
• ✅ Strong artistic style

Future Outlook

2025-2026 Trends

1. MCP Adoption Accelerating

   • OpenAI, Anthropic, and others standardizing on MCP
   • More MCP servers expected in 2025

2. DALL-E Sunset

   • DALL-E 2/3 EOL: May 12, 2026
   • Migrate to GPT Image models now

3. Model Consolidation

   • Fewer, higher-quality models
   • Focus on multi-modal capabilities

4. Free Tier Pressure

   • Free tiers may reduce as costs rise
   • Lock in Google Nano Banana free tier while available

5. Midjourney API Uncertainty

   • Still no official API announced
   • Consider migrating to Flux or Leonardo AI

Summary

Sources

1. ai-image - npm
2. Image Generation using OpenAI API with NodeJs - Medium
3. Dall-E Tool | LangChain
4. Image generation | OpenAI API
5. 2025 Comprehensive Image Generation API Guide - Cursor IDE
6. stable-diffusion-api - npm
7. Exploring the Top Stable Diffusion API Providers in 2025
8. Model Context Protocol Servers - GitHub
9. What Is mcp-image-gen? - Skywork AI
10. New tools and features in the Responses API | OpenAI
11. Top Image Generation & Manipulation MCP Servers
12. MCP Server Finder
13. Imagine.js — AI Image Generator Library for Node.js
14. @google/genai - npm
15. 10 Best Midjourney APIs & Their Cost (Working in 2025)
16. Best Midjourney API Solutions for 2025 - Apiframe
17. The 10 Best Midjourney Alternatives in 2025