复制Flux Mcp

什么是复制流模型的MCP？

复制流模型的MCP是一个创新工具，旨在生成与特定编码氛围和美学风格相符的定制图像和SVG资产。这个强大的应用程序利用AI技术简化视觉资产创建过程，使其成为开发人员在项目中增强定制设计元素的必备资源。

复制流模型的MCP的特点

AI驱动的设计生成：利用先进算法创建独特的视觉资产，以满足用户的特定需求。
自定义选项：提供多种设置以调整生成图像和SVG的风格和外观。
用户友好的界面：以开发人员为中心设计，确保直观体验，减少学习曲线。
集成能力：轻松与现有工作流程和工具集成，实现无缝资产管理。
开源：可供公众使用，鼓励开发者社区的合作和贡献。

如何使用复制流模型的MCP

安装：从GitHub克隆代码库，并按照文档中提供的设置说明进行操作。
配置：调整设置以匹配您所需的美学和编码风格。
生成资产：使用该工具通过输入您的规格来创建图像和SVG。
导出和使用：下载生成的资产，并根据需要将其纳入您的项目中。

常见问题解答

问：复制流模型的MCP是免费使用的吗？

答：是的，该工具是开源的，供公众免费使用。

问：我可以自定义生成的资产吗？

答：当然可以！该工具提供各种自定义选项，以根据您的具体要求调整资产。

问：我如何为该项目做贡献？

答：欢迎贡献！您可以分叉代码库，进行更改，并提交拉取请求以供审核。

问：复制流模型的MCP支持哪些编程语言？

答：该工具设计为支持多种编程语言，使其在不同开发环境中具有多功能性。

问：我在哪里可以找到更多信息或支持？

答：有关更多信息和支持，可以在GitHub上的项目文档中找到。

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/awkoy/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

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

概览

什么是复制流模型的MCP？

复制流模型的MCP的特点

如何使用复制流模型的MCP

常见问题解答

问：复制流模型的MCP是免费使用的吗？

问：我可以自定义生成的资产吗？

问：我如何为该项目做贡献？

问：复制流模型的MCP支持哪些编程语言？

问：我在哪里可以找到更多信息或支持？

详情

Replicate Flux MCP

📑 Table of Contents

🚀 Getting Started & Integration

Setup Process

Cursor Integration

Method 1: Using mcp.json

Method 2: Manual Mode

Claude Desktop Integration

Smithery Integration

Glama.ai Integration

🌟 Features

📚 Documentation

Available Tools

generate_image

generate_multiple_images

generate_image_variants

generate_svg

prediction_list

get_prediction

Available Resources

imagelist

svglist

predictionlist

💻 Development

⚙️ Technical Details

Stack

Configuration

🔍 Troubleshooting

Common Issues

Authentication Error

Safety Filter Triggered

Timeout Error

🤝 Contributing

📄 License

🔗 Resources

🎨 Examples

Batch Image Generation with generate_multiple_images

Image Variants with generate_image_variants

Server配置

项目信息

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