trackmcp
Back to directory
mikeyny

ai-image-gen-mcp

View on GitHub

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

126 stars TypeScriptAI & Machine Learning Updated Sep 11, 2025

Documentation

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:

bash
npm install

3. Add your Replicate API token directly in the code at `src/imageService.ts` by updating the `apiToken` constant:

bash
// 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:

bash
REPLICATE_API_TOKEN=your-replicate-api-token-here

Then build the project:

bash
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
`prompt`stringYes-Text prompt for image generation
`output_dir`stringYes-Server directory path to save generated images
`go_fast`booleanNofalseEnable faster generation mode
`megapixels`stringNo"1"Resolution quality ("1", "2", "4")
`num_outputs`numberNo1Number of images to generate (1-4)
`aspect_ratio`stringNo"1:1"Aspect ratio ("1:1", "4:3", "16:9")
`output_format`stringNo"webp"Image format ("webp", "png", "jpeg")
`output_quality`numberNo80Compression quality (1-100)
`num_inference_steps`numberNo4Number of denoising steps (4-20)

Example Request

json
{
  "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

json
{
  "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

Frequently asked questions

What is ai-image-gen-mcp?

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

How do I install ai-image-gen-mcp?

Open the GitHub repository and follow its README. Most MCP servers are added to your client's MCP config, then called by your agent.

Is ai-image-gen-mcp open source?

Yes — it is hosted on GitHub at https://github.com/mikeyny/ai-image-gen-mcp and has 126 stars.

Related MCP tools

Run your own MCP server? See who uses it and what to fix.

Measure it with TrackMCP