FLUX MCP Server

# FLUX MCP Server & CLI A Model Context Protocol (MCP) server and command-line tool for generating images using FLUX.1-dev with automatic model unloading to save VRAM and power. ## Features - 🎨 **High-Quality Image Generation** - Uses FLUX.1-dev for state-of-the-art image synthesis - ⚡ **Lazy Loading** - Model loads only when needed - 🔄 **Auto-Unload** - Automatically unloads model after configurable inactivity period (MCP mode) - 💾 **Memory Efficient** - Uses bfloat16 for optimal VRAM usage (~12GB) - 🎲 **Reproducible** - Seed-based generation for consistent results - 📊 **Status Monitoring** - Check model status and VRAM usage - 🔧 **Runtime Configuration** - Adjust timeout without restarting - 🖥️ **Dual Interface** - Use via Claude Desktop (MCP) or command-line (CLI) ## Requirements - Python 3.10+ - NVIDIA GPU with 16GB+ VRAM (tested on RTX 4070 Ti Super) - CUDA toolkit installed - PyTorch with CUDA support ## Installation 1. **Clone the repository** (or navigate to the project directory): ```bash cd /path/to/flux-mcp ``` 2. **Install with UV** (recommended): ```bash uv sync ``` Or install with pip: ```bash pip install -e . ``` 3. **Configure environment variables**: ```bash cp .env.example .env # Edit .env with your preferred settings ``` ### Configuration Options Edit `.env` to customize: ```bash # Auto-unload timeout in seconds (default: 300 = 5 minutes) FLUX_UNLOAD_TIMEOUT=300 # Output directory for generated images FLUX_OUTPUT_DIR=/path/to/flux_output # Optional: Custom HuggingFace cache directory # FLUX_MODEL_CACHE=/path/to/cache ``` ## MCP Server Registration Add the server to your Claude Desktop configuration file: **macOS**: `~/Library/Application Support/Claude/claude_desktop_config.json` **Windows**: `%APPDATA%\Claude\claude_desktop_config.json` **Linux**: `~/.config/Claude/claude_desktop_config.json` ```json { "mcpServers": { "flux": { "command": "uv", "args": [ "--directory", "/absolute/path/to/flux-mcp", "run", "flux-mcp" ] } } } ``` Or if installed globally with pip: ```json { "mcpServers": { "flux": { "command": "python", "args": [ "-m", "flux_mcp.server" ] } } } ``` After adding the configuration, restart Claude Desktop. ## CLI Usage In addition to the MCP server for Claude Desktop, you can use FLUX directly from the command line for **completely offline and private** image generation. ### Quick Start ```bash # Basic usage flux generate "a beautiful sunset over mountains" # With custom parameters flux generate "portrait of a cat" --steps 35 --guidance 4.0 --seed 42 # Interactive mode for batch generation flux generate --interactive # Check system status flux status # View configuration flux config # Open output directory flux open-output ``` ### Generate Command The main command for image generation: ```bash flux generate [OPTIONS] PROMPT ``` **Options:** - `--steps, -s INTEGER` - Number of inference steps (default: 28) - `--guidance, -g FLOAT` - Guidance scale (default: 3.5) - `--width, -w INTEGER` - Image width in pixels, must be multiple of 8 (default: 1024) - `--height, -h INTEGER` - Image height in pixels, must be multiple of 8 (default: 1024) - `--seed INTEGER` - Random seed for reproducibility - `--output, -o PATH` - Custom output path (default: auto-generated) - `--output-dir PATH` - Override output directory - `--interactive, -i` - Interactive mode - `--verbose, -v` - Verbose output with debug info **Examples:** ```bash # Simple generation flux generate "a cozy cabin in snowy mountains" # High quality with more steps flux generate "professional portrait" --steps 40 --guidance 7.5 # Custom resolution flux generate "wide landscape" --width 1536 --height 1024 # Reproducible generation flux generate "cute robot" --seed 42 # Save to specific location flux generate "sunset" --output ~/Pictures/my-sunset.png # Interactive mode (best for multiple images) flux generate --interactive ``` ### Interactive Mode Interactive mode allows you to generate multiple images without reloading the model: ```bash flux generate --interactive ``` **Interactive workflow:** 1. Enter your prompt 2. Configure parameters (steps, guidance, dimensions, seed) 3. Image generates and saves 4. Choose to generate another or exit 5. Model stays loaded between generations for faster subsequent images ### Other Commands **Status Command:** ```bash flux status ``` Shows: - Model information - Output directory - CUDA availability - GPU name and VRAM usage - Model cache location **Config Command:** ```bash flux config ``` Displays current configuration from environment variables. **Open Output:** ```bash flux open-output ``` Opens the output directory in your file manager (Linux: xdg-open, macOS: open, Windows: explorer). ### Output Files Generated images are saved with metadata: - **Image:** `flux_YYYYMMDD_HHMMSS_SEED.png` - **Metadata:** `flux_YYYYMMDD_HHMMSS_SEED.json` Metadata JSON contains: ```json { "prompt": "your prompt here", "seed": 42, "steps": 28, "guidance_scale": 3.5, "width": 1024, "height": 1024, "model": "black-forest-labs/FLUX.1-dev", "generation_time_seconds": 15.3, "timestamp": "2025-01-26T12:34:56" } ``` ### CLI vs MCP Server **CLI Mode:** - ✓ Completely offline and private (no Claude Desktop needed) - ✓ Direct control from terminal - ✓ Batch generation with interactive mode - ✓ No auto-unload (process terminates after generation) - ✓ Saves metadata JSON files - ✓ Rich terminal UI with progress bars **MCP Server Mode:** - ✓ Integrated with Claude Desktop - ✓ Natural language interface - ✓ Auto-unload after timeout (saves power) - ✓ Persistent background process - ✓ Access from Claude conversations Both modes share the same configuration, model cache, and output directory. ## MCP Server Tools (Claude Desktop) ### 1. `generate_image` Generate an image from a text prompt. **Parameters:** - `prompt` (required): Text description of the image - `steps` (optional): Number of inference steps (default: 28, range: 20-50) - `guidance_scale` (optional): Guidance scale (default: 3.5, range: 1.0-10.0) - `width` (optional): Image width in pixels (default: 1024, range: 256-2048) - `height` (optional): Image height in pixels (default: 1024, range: 256-2048) - `seed` (optional): Random seed for reproducibility (random if not provided) **Example Usage in Claude:** ``` Generate an image of a futuristic cyberpunk city at sunset with neon lights ``` ``` Generate an image with seed 42 of a serene mountain landscape with steps=30 ``` ### 2. `unload_model` Immediately unload the FLUX model from GPU memory. **Example Usage:** ``` Unload the FLUX model to free up VRAM ``` ### 3. `get_status` Check the current status of the FLUX generator. **Returns:** - Model load status - Time remaining until auto-unload - Current VRAM usage - Last access time **Example Usage:** ``` Check the FLUX model status ``` ### 4. `set_timeout` Change the auto-unload timeout at runtime. **Parameters:** - `timeout_seconds` (required): New timeout in seconds (0 to disable) **Example Usage:** ``` Set FLUX auto-unload timeout to 600 seconds ``` ``` Disable FLUX auto-unload ``` ## Usage Examples ### Basic Image Generation ``` Generate an image: "A majestic dragon flying over a medieval castle" ``` The server will: 1. Load the FLUX model (if not already loaded) 2. Generate the image 3. Save it to the output directory as `YYYYMMDD_HHMMSS_{seed}.png` 4. Return the file path, seed, and generation settings 5. Schedule auto-unload after 5 minutes (default) ### Reproducible Generation To generate the same image again, use the seed from a previous generation: ``` Generate an image with seed 12345: "A cute robot playing with a kitten" ``` ### Custom Parameters ``` Generate a portrait with steps=40, guidance_scale=7.5, width=768, height=1024: "Professional headshot of a business executive" ``` ### Memory Management Check current status: ``` What's the FLUX model status? ``` Manually unload to free VRAM: ``` Unload the FLUX model ``` Adjust auto-unload timeout: ``` Set FLUX timeout to 10 minutes ``` ## How It Works ### Auto-Unload Mechanism 1. **Lazy Loading**: The model is NOT loaded when the server starts 2. **On-Demand Loading**: Model loads automatically on first generation request 3. **Timer Reset**: Each generation resets the auto-unload timer 4. **Automatic Cleanup**: After the configured timeout with no activity: - Model is removed from memory - GPU cache is cleared (`torch.cuda.empty_cache()`) - Python garbage collection runs 5. **Seamless Reload**: Model automatically reloads on next request ### Memory Management The server uses several strategies to minimize VRAM usage: - **bfloat16 precision** instead of float32 (saves ~50% VRAM) - **Explicit cache clearing** when unloading - **Threading** for non-blocking auto-unload - **Lock-based synchronization** for thread-safe operation ### Output Files Generated images are saved as: ``` {FLUX_OUTPUT_DIR}/{timestamp}_{seed}.png ``` Example: `20250126_143052_42.png` ## Troubleshooting ### CUDA Out of Memory **Problem**: Error during generation: "CUDA out of memory" **Note**: The generator automatically uses **sequential CPU offloading** to reduce VRAM usage from ~28GB to ~12GB. This should work on 16GB GPUs like RTX 4070 Ti Super. **If you still get OOM errors:** 1. **Close other GPU applications**: ```bash # Check what's using VRAM nvidia-smi ``` 2. **Reduce image dimensions**: ```bash flux generate "prompt" --width 768 --height 768 # Or even smaller flux generate "prompt" --width 512 --height 512 ``` 3. **Reduce inference steps**: ```bash flux generate "prompt" --steps 20 # Default is 28 ``` 4. **Restart the process** if VRAM isn't fully freed: ```bash # CLI: Just run again (process exits after generation) # MCP: Restart Claude Desktop ``` ### Model Download Issues **Problem**: Model download fails or times out **Solutions**: 1. Check internet connection 2. Set a custom cache directory with more space: ```bash FLUX_MODEL_CACHE=/path/to/large/disk/cache ``` 3. Download manually with HuggingFace CLI: ```bash huggingface-cli download black-forest-labs/FLUX.1-dev ``` ### Server Not Responding **Problem**: Claude Desktop doesn't see the tools **Solutions**: 1. Check Claude Desktop logs for errors 2. Verify the configuration path is absolute 3. Ensure UV is in PATH or use full path to UV binary 4. Restart Claude Desktop after config changes 5. Test the server manually: ```bash cd /path/to/flux-mcp uv run flux-mcp ``` ### Slow Generation **Problem**: Image generation takes too long **Solutions**: 1. Reduce `steps` parameter (try 20-25 instead of 28) 2. Ensure GPU is being used (check with `nvidia-smi`) 3. Close background applications to free GPU resources 4. Check that CUDA is properly installed ### Permission Errors **Problem**: Cannot write to output directory **Solutions**: 1. Check directory permissions 2. Set a different output directory in `.env`: ```bash FLUX_OUTPUT_DIR=/home/$USER/flux_output ``` 3. Create the directory manually: ```bash mkdir -p ~/flux_output chmod 755 ~/flux_output ``` ## Advanced Configuration ### Custom Model Cache To share the model cache across multiple projects or save space: ```bash # In .env FLUX_MODEL_CACHE=/mnt/data/huggingface/cache ``` ### Disable Auto-Unload To keep the model loaded permanently (uses more power but faster): ```bash # In .env FLUX_UNLOAD_TIMEOUT=0 ``` Or at runtime: ``` Set FLUX timeout to 0 ``` ### Logging The server logs to stderr. To capture logs: ```json { "mcpServers": { "flux": { "command": "sh", "args": [ "-c", "cd /path/to/flux-mcp && uv run flux-mcp 2>> /tmp/flux-mcp.log" ] } } } ``` ## Performance Tips ### Optimal Settings for RTX 4070 Ti Super (16GB) - **Resolution**: Up to 1024x1024 comfortably - **Steps**: 25-30 for good quality - **Batch size**: 1 (model doesn't support batching well) - **Timeout**: 300s for occasional use, 600s for active sessions ### Generation Time Expectations - **1024x1024, 28 steps**: ~20-40 seconds (depending on prompt complexity) - **512x512, 20 steps**: ~5-10 seconds - **First generation**: +10-15 seconds for model loading ## Technical Details ### Architecture ``` flux-mcp/ ├── src/flux_mcp/ │ ├── __init__.py # Package metadata │ ├── config.py # Environment configuration (shared) │ ├── generator.py # FluxGenerator class (shared) │ ├── server.py # MCP server (tool handlers) │ └── cli.py # CLI tool ├── pyproject.toml # Project dependencies ├── .env # Local configuration └── README.md # This file ``` ### Key Components - **FluxGenerator**: Manages model lifecycle, threading, and GPU memory (shared between CLI and MCP) - **Config**: Loads environment variables and provides defaults (shared) - **MCP Server**: Exposes tools via Model Context Protocol for Claude Desktop - **CLI Tool**: Direct command-line interface for offline usage ### Thread Safety The generator uses a threading lock (`threading.Lock`) to ensure: - Only one generation at a time - Safe model loading/unloading - No race conditions with auto-unload timer ## License MIT License - see LICENSE file for details ## Contributing Contributions welcome! Please: 1. Fork the repository 2. Create a feature branch 3. Make your changes 4. Submit a pull request ## Support For issues and questions: - Check the Troubleshooting section above - Review server logs for errors - Open an issue on GitHub ## Changelog ### v0.1.0 (2025-01-26) - Initial release - FLUX.1-dev integration - Auto-unload functionality (MCP mode) - Four MCP tools (generate, unload, status, set_timeout) - CLI tool with interactive mode (`flux` command) - Shared architecture between CLI and MCP server - Comprehensive documentation with CLI and MCP usage examples