Replicate Flux MCP

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Replicate Flux MCP is an advanced Model Context Protocol (MCP) server that empowers AI assistants to generate high-quality images and vector graphics. Leveraging Black Forest Labs' Flux Schnell model for raster images and Recraft's V3 SVG model for vector graphics via the Replicate API.

📑 Table of Contents

Getting Started & Integration
Features
Documentation
- Available Tools
- Available Resources
Development
Technical Details
Troubleshooting
Contributing
License
Resources
Examples

🚀 Getting Started & Integration

Setup Process

Obtain a Replicate API Token
- Sign up at Replicate
- Create an API token in your account settings
Choose Your Integration Method
- Follow one of the integration options below based on your preferred MCP client
Ask Your AI Assistant to Generate an Image
- Simply ask naturally: "Can you generate an image of a serene mountain landscape at sunset?"
- Or be more specific: "Please create an image showing a peaceful mountain scene with a lake reflecting the sunset colors in the foreground"
Explore Advanced Features
- Try different parameter settings for customized results
- Experiment with SVG generation using generate_svg
- Use batch image generation or variant generation features

Cursor Integration

Method 1: Using mcp.json

Create or edit the .cursor/mcp.json file in your project directory:

{
  "mcpServers": {
    "replicate-flux-mcp": {
      "command": "env REPLICATE_API_TOKEN=YOUR_TOKEN npx",
      "args": ["-y", "replicate-flux-mcp"]
    }
  }
}

Replace YOUR_TOKEN with your actual Replicate API token
Restart Cursor to apply the changes

Method 2: Manual Mode

Open Cursor and go to Settings
Navigate to the "MCP" or "Model Context Protocol" section
Click "Add Server" or equivalent
Enter the following command in the appropriate field:

env REPLICATE_API_TOKEN=YOUR_TOKEN npx -y replicate-flux-mcp

Replace YOUR_TOKEN with your actual Replicate API token
Save the settings and restart Cursor if necessary

Claude Desktop Integration

Create or edit the mcp.json file in your configuration directory:

{
  "mcpServers": {
    "replicate-flux-mcp": {
      "command": "npx",
      "args": ["-y", "replicate-flux-mcp"],
      "env": {
        "REPLICATE_API_TOKEN": "YOUR TOKEN"
      }
    }
  }
}

Replace YOUR_TOKEN with your actual Replicate API token
Restart Claude Desktop to apply the changes

Smithery Integration

This MCP server is available as a hosted service on Smithery, allowing you to use it without setting up your own server.

Visit Smithery and create an account if you don't have one
Navigate to the Replicate Flux MCP server page
Click "Add to Workspace" to add the server to your Smithery workspace
Configure your MCP client (Cursor, Claude Desktop, etc.) to use your Smithery workspace URL

For more information on using Smithery with your MCP clients, visit the Smithery documentation.

Glama.ai Integration

This MCP server is also available as a hosted service on Glama.ai, providing another option to use it without local setup.

Visit Glama.ai and create an account if you don't have one
Go to the Replicate Flux MCP server page
Click "Install Server" to add the server to your workspace
Configure your MCP client to use your Glama.ai workspace

For more information, visit the Glama.ai MCP servers documentation.

🌟 Features

🖼️ High-Quality Image Generation - Create stunning images using Flux Schnell, a state-of-the-art AI model
🎨 Vector Graphics Support - Generate professional SVG vector graphics with Recraft V3 SVG model
🤖 AI Assistant Integration - Seamlessly enable AI assistants like Claude to generate visual content
🎛️ Advanced Customization - Fine-tune generation with controls for aspect ratio, quality, resolution, and more
🔌 Universal MCP Compatibility - Works with all MCP clients including Cursor, Claude Desktop, Cline, and Zed
🔒 Secure Local Processing - All requests are processed locally for enhanced privacy and security
🔍 Comprehensive History Management - Track, view, and retrieve your complete generation history
📊 Batch Processing - Generate multiple images from different prompts in a single request
🔄 Variant Exploration - Create and compare multiple interpretations of the same concept
✏️ Prompt Engineering - Fine-tune image variations with specialized prompt modifications

📚 Documentation

Available Tools

`generate_image`

Generates an image based on a text prompt using the Flux Schnell model.

{
  prompt: string;                // Required: Text description of the image to generate
  seed?: number;                 // Optional: Random seed for reproducible generation
  go_fast?: boolean;             // Optional: Run faster predictions with optimized model (default: true)
  megapixels?: "1" | "0.25";     // Optional: Image resolution (default: "1")
  num_outputs?: number;          // Optional: Number of images to generate (1-4) (default: 1)
  aspect_ratio?: string;         // Optional: Aspect ratio (e.g., "16:9", "4:3") (default: "1:1")
  output_format?: string;        // Optional: Output format ("webp", "jpg", "png") (default: "webp")
  output_quality?: number;       // Optional: Image quality (0-100) (default: 80)
  num_inference_steps?: number;  // Optional: Number of denoising steps (1-4) (default: 4)
  disable_safety_checker?: boolean; // Optional: Disable safety filter (default: false)
}

`generate_multiple_images`

Generates multiple images based on an array of prompts using the Flux Schnell model.

{
  prompts: string[];             // Required: Array of text descriptions for images to generate (1-10 prompts)
  seed?: number;                 // Optional: Random seed for reproducible generation
  go_fast?: boolean;             // Optional: Run faster predictions with optimized model (default: true)
  megapixels?: "1" | "0.25";     // Optional: Image resolution (default: "1")
  aspect_ratio?: string;         // Optional: Aspect ratio (e.g., "16:9", "4:3") (default: "1:1")
  output_format?: string;        // Optional: Output format ("webp", "jpg", "png") (default: "webp")
  output_quality?: number;       // Optional: Image quality (0-100) (default: 80)
  num_inference_steps?: number;  // Optional: Number of denoising steps (1-4) (default: 4)
  disable_safety_checker?: boolean; // Optional: Disable safety filter (default: false)
}

`generate_image_variants`

Generates multiple variants of the same image from a single prompt.

{
  prompt: string;                // Required: Text description for the image to generate variants of
  num_variants: number;          // Required: Number of image variants to generate (2-10, default: 4)
  prompt_variations?: string[];  // Optional: List of prompt modifiers to apply to variants (e.g., ["in watercolor style", "in oil painting style"])
  variation_mode?: "append" | "replace"; // Optional: How to apply variations - 'append' adds to base prompt, 'replace' uses variations directly (default: "append")
  seed?: number;                 // Optional: Base random seed. Each variant will use seed+variant_index
  go_fast?: boolean;             // Optional: Run faster predictions with optimized model (default: true)
  megapixels?: "1" | "0.25";     // Optional: Image resolution (default: "1")
  aspect_ratio?: string;         // Optional: Aspect ratio (e.g., "16:9", "4:3") (default: "1:1")
  output_format?: string;        // Optional: Output format ("webp", "jpg", "png") (default: "webp")
  output_quality?: number;       // Optional: Image quality (0-100) (default: 80)
  num_inference_steps?: number;  // Optional: Number of denoising steps (1-4) (default: 4)
  disable_safety_checker?: boolean; // Optional: Disable safety filter (default: false)
}

`generate_svg`

Generates an SVG vector image based on a text prompt using the Recraft V3 SVG model.

{
  prompt: string;                // Required: Text description of the SVG to generate
  size?: string;                 // Optional: Size of the generated SVG (default: "1024x1024")
  style?: string;                // Optional: Style of the generated image (default: "any")
                                // Options: "any", "engraving", "line_art", "line_circuit", "linocut"
}

`prediction_list`

Retrieves a list of your recent predictions from Replicate.

{
  limit?: number;  // Optional: Maximum number of predictions to return (1-100) (default: 50)
}

`get_prediction`

Gets detailed information about a specific prediction.

{
  predictionId: string;  // Required: ID of the prediction to retrieve
}

Available Resources

`imagelist`

Browse your history of generated images created with the Flux Schnell model.

`svglist`

Browse your history of generated SVG images created with the Recraft V3 SVG model.

`predictionlist`

Browse all your Replicate predictions history.

💻 Development

Clone the repository:

git clone https://github.com/yourusername/replicate-flux-mcp.git
cd replicate-flux-mcp

Install dependencies:

npm install

Start development mode:

npm run dev

Build the project:

npm run build

Connect to Client:

{
  "mcpServers": {
    "image-generation-mcp": {
      "command": "npx",
      "args": [
        "/Users/{USERNAME}/{PATH_TO}/replicate-flux-mcp/build/index.js"
      ],
      "env": {
        "REPLICATE_API_TOKEN": "YOUR REPLICATE API TOKEN"
      }
    }
  }
}

⚙️ Technical Details

Stack

Model Context Protocol SDK - Core MCP functionality for tool and resource management
Replicate API - Provides access to state-of-the-art AI image generation models
TypeScript - Ensures type safety and leverages modern JavaScript features
Zod - Implements runtime type validation for robust API interactions

Configuration

The server can be configured by modifying the CONFIG object in src/config/index.ts:

const CONFIG = {
  serverName: "replicate-flux-mcp",
  serverVersion: "0.1.2",
  imageModelId: "black-forest-labs/flux-schnell",
  svgModelId: "recraft-ai/recraft-v3-svg",
  pollingAttempts: 25,
  pollingInterval: 2000, // ms
};

🔍 Troubleshooting

Common Issues

Authentication Error

Ensure your REPLICATE_API_TOKEN is correctly set in the environment
Verify your token is valid by testing it with the Replicate API directly

Safety Filter Triggered

The model has a built-in safety filter that may block certain prompts
Try modifying your prompt to avoid potentially problematic content

Timeout Error

For larger images or busy servers, you might need to increase pollingAttempts or pollingInterval in the configuration
Default settings should work for most use cases

🤝 Contributing

Contributions are welcome! Please follow these steps to contribute:

Fork the repository
Create your feature branch (git checkout -b feature/amazing-feature)
Commit your changes (git commit -m 'Add some amazing feature')
Push to the branch (git push origin feature/amazing-feature)
Open a Pull Request

For feature requests or bug reports, please create a GitHub issue. If you like this project, consider starring the repository!

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🔗 Resources

🎨 Examples

Demo

| Multiple Prompts | Prompt Variants | |-----------------|-----------------| | Multiple prompts example: "A serene mountain lake at sunset", "A bustling city street at night", "A peaceful garden in spring" | Variants example: Base prompt "A majestic castle" with modifiers "in watercolor style", "as an oil painting", "with gothic architecture" |

Here are some examples of how to use the tools:

Batch Image Generation with `generate_multiple_images`

Create multiple distinct images at once with different prompts:

{
  "prompts": [
    "A red sports car on a mountain road", 
    "A blue sports car on a beach", 
    "A vintage sports car in a city street"
  ]
}

Image Variants with `generate_image_variants`

Create different interpretations of the same concept using seeds:

{
  "prompt": "A futuristic city skyline at night",
  "num_variants": 4,
  "seed": 42
}

Or explore style variations with prompt modifiers:

{
  "prompt": "A character portrait",
  "prompt_variations": [
    "in anime style", 
    "in watercolor style", 
    "in oil painting style", 
    "as a 3D render"
  ]
}

Made with ❤️ by Yaroslav Boiko