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Flux Image Generator

Flux Image Generator

Local
github.com/frankdenoDeveloper Tools1Updated 84w ago

About Flux Image Generator

Flux Image Generator is an MCP server that creates images with Black Forest Lab's FLUX model. It supports single and batch generation, with configurable image settings and local saving.

Key features

  1. 01Generate images from text prompts
  2. 02Adjust dimensions and safety settings
  3. 03Upsample prompts and set seeds
  4. 04Generate images in batches
  5. 05Save generated images locally

Use cases

  1. 01Creating images from descriptive prompts
  2. 02Generating several images from a prompt list
  3. 03Tuning output dimensions and safety tolerance

MCP support

It exposes generateImage, quickImage, and batchGenerateImages tools to MCP clients for generating images with FLUX.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

FLUX Image Generator MCP Server

An MCP (Model Context Protocol) server for generating images using Black Forest Lab's FLUX model. Uses the latest MCP SDK (v1.7.0).

Features

  • Generate images based on text prompts
  • Customize image dimensions, prompt upsampling, and safety settings
  • Save generated images locally
  • Batch image generation from multiple prompts

Prerequisites

Installation

From Source
  1. Clone this repository
  2. Install dependencies:
npm install
  1. Create a .env file based on .env.example and add your Black Forest Lab API key:
BFL_API_KEY=your_api_key_here
  1. Build the project:
npm run build
Using npm
npm install -g @modelcontextprotocol/server-flux-image-generator

Usage

Starting the MCP Server

Start the server with:

npm start

For development with auto-recompilation:

npm run watch
Integrating with MCP Clients

To use this server with MCP clients (like Claude), add the following to your client's configuration:

{
  "mcpServers": {
    "flux-image-generator": {
      "command": "mcp-server-flux-image-generator",
      "env": {
        "BFL_API_KEY": "your_api_key_here"
      }
    }
  }
}

Available Tools

generateImage

Generates an image based on a text prompt with customizable settings.

Parameters:

  • prompt (string, required): Text description of the image to generate
  • width (number, optional, default: 1024): Width of the image in pixels
  • height (number, optional, default: 1024): Height of the image in pixels
  • promptUpsampling (boolean, optional, default: false): Enhance detail by upsampling the prompt
  • seed (number, optional): Random seed for reproducible results
  • safetyTolerance (number, optional, default: 3): Content moderation tolerance (1-5)

Example:

{
  "prompt": "A serene lake at sunset with mountains in the background",
  "width": 1024,
  "height": 768,
  "promptUpsampling": true,
  "seed": 12345,
  "safetyTolerance": 3
}
quickImage

A simplified tool for quickly generating images with default settings.

Parameters:

  • prompt (string, required): Text description of the image to generate

Example:

{
  "prompt": "A futuristic cityscape with flying cars"
}
batchGenerateImages

Generates multiple images from a list of prompts.

Parameters:

  • prompts (array of strings, required): List of text prompts (maximum 10)
  • width (number, optional, default: 1024): Width of the images
  • height (number, optional, default: 1024): Height of the images

Example:

{
  "prompts": [
    "A serene lake at sunset",
    "A futuristic cityscape",
    "A magical forest with glowing plants"
  ],
  "width": 1024,
  "height": 768
}

Output Format

All tools return responses in this format:

{
  "image_url": "https://storage.example.com/generated_image.jpg",
  "local_path": "/path/to/output/flux_1234567890.png"
}

For errors:

{
  "error": true,
  "message": "Error description"
}

The batch tool returns:

{
  "total": 3,
  "successful": 2,
  "failed": 1,
  "results": [
    {
      "prompt": "A serene lake at sunset",
      "success": true,
      "image_url": "https://storage.example.com/image1.jpg",
      "local_path": "/path/to/output/flux_batch_1234567890_0.png"
    },
    {
      "prompt": "A futuristic cityscape",
      "success": true,
      "image_url": "https://storage.example.com/image2.jpg",
      "local_path": "/path/to/output/flux_batch_1234567890_1.png"
    },
    {
      "prompt": "Prohibited content",
      "success": false,
      "error": "Content policy violation"
    }
  ]
}

License

MIT

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.