BFL_mcp_server

lucas120301/BFL_mcp_server

3.1

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Flux MCP Server is an AI-powered image generation server using Black Forest Labs' Flux models, designed for seamless integration with AI agents and optimized for Dedalus Labs deployment.

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Flux MCP Server

An MCP (Model Context Protocol) server for AI-powered image generation using Black Forest Labs' Flux models. Built for seamless integration with AI agents and compatible with Dedalus Labs deployment.

Features

  • AI Image Generation: Generate high-quality images using state-of-the-art Flux models
  • Multiple Models: Support for different Flux model variants (flux-pro-1.1, flux-dev, flux-schnell)
  • Flexible Parameters: Customizable aspect ratios, dimensions, and safety settings
  • MCP Integration: Seamless integration with MCP-compatible AI agents
  • Dedalus Ready: Optimized for deployment on Dedalus Labs platform
  • Rate Limiting: Built-in protection for API keys and usage limits

Quick Start

Prerequisites

  • Python 3.8+
  • uv package manager
  • Black Forest Labs API key from api.bfl.ai

Installation

  1. Clone the repository:

    git clone <repository-url>
cd flux-mcp-main

  2. Install dependencies:

    # Install uv package manager
brew install uv  # or pip install uv

# Install dependencies
uv sync --no-dev

  3. Configure API key:

    # Set environment variable
export BFL_API_KEY="your_api_key_here"

# Or create .env file
cp config/.env.example config/.env
# Edit config/.env and add your API key

  4. Run the server:

    uv run main

Available Tools

flux_generate

Generate images using Flux AI models.

Parameters:

  • prompt (string, required): Text description of the image to generate
  • model (string, optional): Flux model to use (default: "flux-pro-1.1")
  • aspect_ratio (string, optional): Image aspect ratio (default: "16:9")
  • width (int, optional): Image width in pixels (default: 1024)
  • height (int, optional): Image height in pixels (default: 1024)
  • raw (bool, optional): Use raw mode for more creative outputs (default: false)
  • safety_tolerance (int, optional): Safety filter level 0-10 (default: 6)
  • prompt_upsampling (bool, optional): Enhance prompt quality (default: false)

Returns:

  • status: "success" or "error"
  • image: URL to the generated image (on success)
  • meta: Metadata about the generation (on success)
  • message: Error message (on error)

Example Usage

# Generate a simple image
result = await flux_generate(
    prompt="A beautiful sunset over mountains",
    aspect_ratio="16:9"
)

# Generate with custom parameters
result = await flux_generate(
    prompt="A futuristic cityscape at night",
    model="flux-pro-1.1",
    width=1920,
    height=1080,
    safety_tolerance=4,
    prompt_upsampling=True
)

Supported Models

  • flux-pro-1.1: Latest Flux Pro model (recommended)
  • flux-dev: Development model
  • flux-schnell: Fast generation model

Aspect Ratios

Common aspect ratios supported:

  • 1:1 - Square
  • 16:9 - Widescreen
  • 9:16 - Portrait
  • 4:3 - Standard
  • 3:4 - Portrait standard

Deployment

Deploy to Dedalus Labs

  1. Set Environment Variables in Dedalus UI:

    • BFL_API_KEY: Your Black Forest Labs API key (required)

  2. Deploy:

    dedalus deploy . --name "flux-image-generator"

  3. Test:

    dedalus test flux-image-generator

Local Development

# Test locally
./scripts/test-local.sh

# Deploy to Dedalus
./scripts/deploy.sh

Project Structure

flux-mcp-main/
├── main.py                 # Entry point (required by Dedalus)
├── pyproject.toml          # Package configuration
├── src/
│   ├── main.py            # MCP server implementation
│   └── flux_adapter.py    # Black Forest Labs API adapter
├── config/
│   └── .env.example       # Environment template
├── docs/                  # Documentation
│   ├── getting-started.md
│   ├── deployment.md
│   └── api-reference.md
├── examples/              # Usage examples
│   ├── basic-usage.py
│   ├── creative-prompts.py
│   └── README.md
├── scripts/               # Deployment scripts
│   ├── deploy.sh
│   └── test-local.sh
└── tests/                 # Test files
    └── image_generation.py

Documentation

Examples

Check out the directory for:

  • - Simple image generation
  • - Advanced prompt techniques

Safety and Guidelines

  • The safety_tolerance parameter controls content filtering (0-10)
  • Higher values are more restrictive
  • Use appropriate prompts that comply with Black Forest Labs' usage policies
  • Generated images are subject to the API provider's terms of service

Troubleshooting

Common Issues

  1. API Key Not Set

    • Ensure BFL_API_KEY environment variable is set
    • Check that your API key is valid and active

  2. Generation Timeout

    • Complex prompts may take longer to process
    • Try simplifying your prompt or using a different model

  3. Safety Filter Triggered

    • Adjust safety_tolerance parameter
    • Modify your prompt to be more appropriate

Getting Help

Contributing

  1. Fork the repository
  2. Create a feature branch
  3. Make your changes
  4. Add tests if applicable
  5. Submit a pull request

License

MIT License - see file for details.

Acknowledgments