複製 Flux Mcp

MCP for Replicate Flux Model 是什麼？

MCP for Replicate Flux Model 是一個創新的工具，旨在生成與特定編碼風格和美學風格相符的自定義圖像和 SVG 資產。這個強大的應用程序利用 AI 技術來簡化視覺資產創建過程，使其成為開發人員在項目中增強設計元素的必備資源。

MCP for Replicate Flux Model 的特點

• AI 驅動的設計生成：利用先進的算法創建獨特的視覺資產，以滿足用戶的具體需求。
• 自定義選項：提供多種設置來調整生成圖像和 SVG 的風格和外觀。
• 用戶友好的界面：專為開發人員設計，確保直觀的體驗，最小化學習曲線。
• 集成能力：輕鬆與現有工作流程和工具集成，實現無縫的資產管理。
• 開源：可供公眾使用，鼓勵開發者社區的合作和貢獻。

如何使用 MCP for Replicate Flux Model

1. 安裝：從 GitHub 克隆庫並按照文檔中的設置說明進行操作。
2. 配置：調整設置以匹配您所需的美學和編碼風格。
3. 生成資產：使用該工具通過輸入您的規格來創建圖像和 SVG。
4. 匯出和使用：下載生成的資產，並根據需要將其納入您的項目中。

常見問題解答

問：MCP for Replicate Flux Model 是免費使用的嗎？

答：是的，該工具是開源的，公眾可以免費使用。

問：我可以自定義生成的資產嗎？

答：當然可以！該工具提供多種自定義選項，以便根據您的具體需求調整資產。

問：我如何為該項目做出貢獻？

答：歡迎貢獻！您可以分叉庫，進行更改，並提交拉取請求以供審核。

問：MCP for Replicate Flux Model 支持哪些編程語言？

答：該工具旨在與多種編程語言一起使用，使其在不同的開發環境中具有多功能性。

問：我可以在哪裡找到更多信息或支持？

答：有關更多信息和支持，可以在 GitHub 上的項目文檔中找到。

Replicate Flux MCP

<a href="https://glama.ai/mcp/servers/ss8n1knen8"> <img width="380" height="200" src="https://glama.ai/mcp/servers/ss8n1knen8/badge" /> </a>

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
  • Setup Process
  • Cursor Integration
  • Claude Desktop Integration
  • Smithery Integration
  • Glama.ai Integration
• Features
• Documentation
  • Available Tools
  • Available Resources
• Development
• Technical Details
• Troubleshooting
• Contributing
• License
• Resources
• Examples

🚀 Getting Started & Integration

Setup Process

1. Obtain a Replicate API Token

   • Sign up at Replicate
   • Create an API token in your account settings

2. Choose Your Integration Method

   • Follow one of the integration options below based on your preferred MCP client

3. 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"

4. 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

1. 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"]
    }
  }
}

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

Method 2: Manual Mode

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

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

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

Claude Desktop Integration

1. 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"
      }
    }
  }
}

2. Replace YOUR_TOKEN with your actual Replicate API token
3. 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.

1. Visit Smithery and create an account if you don't have one
2. Navigate to the Replicate Flux MCP server page
3. Click "Add to Workspace" to add the server to your Smithery workspace
4. 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.

1. Visit Glama.ai and create an account if you don't have one
2. Go to the Replicate Flux MCP server page
3. Click "Install Server" to add the server to your workspace
4. 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

1. Clone the repository:

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

2. Install dependencies:

npm install

3. Start development mode:

npm run dev

4. Build the project:

npm run build

5. 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:

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. 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

• Model Context Protocol Documentation
• Replicate API Documentation
• Flux Schnell Model
• Recraft V3 SVG Model
• MCP TypeScript SDK
• Smithery Documentation
• Glama.ai MCP Servers

🎨 Examples

Multiple Prompts	Prompt Variants

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