ai image gen mcp

Local 2025-09-01 00:14:16 0
Image And Video Processing @mikeyny/ai-image-gen-mcp

Enables users to generate images from text prompts using Replicate's model, with configurable parameters and full MCP protocol compliance.

An MCP (Model Context Protocol) server implementation for generating images using Replicate's black-forest-labs/flux-schnell model.

Ideally to be used with Cursor's MCP feature, but can be used with any MCP client.

Features

  • Generate images from text prompts
  • Configurable image parameters (resolution, aspect ratio, quality)
  • Save generated images to specified directory
  • Full MCP protocol compliance
  • Error handling and validation

Prerequisites

  • Node.js 16+
  • Replicate API token
  • TypeScript SDK for MCP

Setup

  1. Clone the repository
  2. Install dependencies: 
    npm install
  3. Add your Replicate API token directly in the code at src/imageService.ts by updating the apiToken constant: 
    // No environment variables are used since they can't be easily set in cursor
const apiToken = "your-replicate-api-token-here";

Note: If using with Claude, you can create a .env file in the root directory and set your API token there: 

REPLICATE_API_TOKEN=your-replicate-api-token-here

Then build the project: 

npm run build

Usage

To use with cursor: 1. Go to Settings 2. Select Features 3. Scroll down to "MCP Servers" 4. Click "Add new MCP Server" 5. Set Type to "Command" 6. Set Command to: node ./path/to/dist/server.js

API Parameters

Parameter Type Required Default Description
prompt string Yes - Text prompt for image generation
output_dir string Yes - Server directory path to save generated images
go_fast boolean No false Enable faster generation mode
megapixels string No "1" Resolution quality ("1", "2", "4")
num_outputs number No 1 Number of images to generate (1-4)
aspect_ratio string No "1:1" Aspect ratio ("1:1", "4:3", "16:9")
output_format string No "webp" Image format ("webp", "png", "jpeg")
output_quality number No 80 Compression quality (1-100)
num_inference_steps number No 4 Number of denoising steps (4-20)

Example Request

{
  "prompt": "black forest gateau cake spelling out 'FLUX SCHNELL'",
  "output_dir": "/var/output/images",
  "filename": "black_forest_cake",
  "output_format": "webp"
  "go_fast": true,
  "megapixels": "1",
  "num_outputs": 2,
  "aspect_ratio": "1:1"
}

Example Response

{
  "image_paths": [
    "/var/output/images/output_0.webp",
    "/var/output/images/output_1.webp"
  ],
  "metadata": {
    "model": "black-forest-labs/flux-schnell",
    "inference_time_ms": 2847
  }
}

Error Handling

The server handles the following error types:

  • Validation errors (invalid parameters)
  • API errors (Replicate API issues)
  • Server errors (filesystem, permissions)
  • Unknown errors (unexpected issues)

Each error response includes: - Error code - Human-readable message - Detailed error information

License

ISC