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ai image gen mcp

Discover the AI Image Generation MCP server for creating images from text prompts with full MCP compliance and customizable parameters.

Introduction

Image Generation MCP Server

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
ParameterTypeRequiredDefaultDescription
promptstringYes-Text prompt for image generation
output_dirstringYes-Server directory path to save generated images
go_fastbooleanNofalseEnable faster generation mode
megapixelsstringNo"1"Resolution quality ("1", "2", "4")
num_outputsnumberNo1Number of images to generate (1-4)
aspect_ratiostringNo"1:1"Aspect ratio ("1:1", "4:3", "16:9")
output_formatstringNo"webp"Image format ("webp", "png", "jpeg")
output_qualitynumberNo80Compression quality (1-100)
num_inference_stepsnumberNo4Number 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

Installation

Add MCP Server
Cursor
Name:generate-image
Type:command
Command:node /Volumes/ExtremeSSD/MCP/ai-image-gen-mcp/dist/server.js

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