What is Webperfect Mcp Server

WebPerfect is a modern MCP server designed for advanced image optimization. It utilizes AI algorithms to enhance images while significantly reducing their file sizes without sacrificing visual quality, making it ideal for web applications.

Use cases

WebPerfect is useful for web developers and designers who need to process large batches of images for websites, ensuring that they are optimized for quick loading times. It can handle various image formats and is perfect for responsive design needs.

How to use

To use WebPerfect, clone the repository, install the dependencies using npm, build the server, and then configure it within your MCP settings. Once the server is running, you can process images by providing input and output directories, or access statistics through specific API calls.

Key features

Key features of WebPerfect include intelligent image processing with AI-driven enhancements, maximum file size reduction of up to 80%, batch automation for processing entire directories, and web-optimized output formats like WebP.

Where to use

WebPerfect can be used in various web contexts, such as in content management systems, e-commerce platforms, or any online service where high-quality images are needed. It is particularly beneficial for services needing to balance quality and performance on the web.

✨ Overview

WebPerfect is a cutting-edge MCP server that revolutionizes image optimization for the web. Using advanced AI algorithms and sophisticated processing techniques, it automatically enhances your images while dramatically reducing file sizes - all without compromising visual quality.

🚀 Key Benefits

• Intelligent Processing: AI-powered algorithms adapt to each image’s unique characteristics
• Superior Quality: Enhanced visual clarity with smart sharpening and noise reduction
• Maximum Compression: Achieve up to 80% size reduction while preserving image quality
• Batch Automation: Process entire directories with a single command
• Web Optimized: Perfect for modern web applications and responsive designs

🛠 Features

🔄 Advanced Image Processing Pipeline

1. Strong noise reduction using median filtering
2. Intelligent auto levels and curves based on image entropy
3. Advanced texture enhancement with modulation and sharpening
4. Smart resolution optimization (up to 4K)
5. Optimized WebP conversion

🔧 Tools

📦 process_images

Effortlessly process and optimize entire image collections with our advanced enhancement pipeline.

{
  inputDir: string;      // Directory containing input images
  outputDir: string;     // Directory for optimized output
}

📊 Resources

📈 Resource Templates

• logs/{date}: Access processing logs by date (YYYY-MM-DD)

  {
    "date": "2024-01-20",
    "entries": [
      {
        "timestamp": "2024-01-20T10:00:00Z",
        "imagesProcessed": 15,
        "totalInputSize": "5.2MB",
        "totalOutputSize": "1.1MB",
        "compressionRatio": "78.8%",
        "averageProcessingTime": "1.2s"
      }
    ]
  }
  

• stats/monthly/{month}: Monthly statistics (YYYY-MM)

  {
    "month": "2024-01",
    "totalImagesProcessed": 450,
    "averageCompressionRatio": "82%",
    "popularFormats": {
      "input": [
        "JPEG",
        "PNG"
      ],
      "output": [
        "WebP"
      ]
    },
    "totalStorageSaved": "150MB"
  }
  

Static Resources

• stats/summary: Overall processing statistics

  {
    "totalImagesProcessed": 5280,
    "averageCompressionRatio": "81%",
    "totalStorageSaved": "1.8GB",
    "popularEnhancements": [
      "noise_reduction",
      "auto_levels_curves",
      "texture_enhancement"
    ],
    "performanceMetrics": {
      "averageProcessingTime": "1.5s",
      "peakThroughput": "45 images/minute"
    }
  }
  

• config/optimization-presets: Available optimization presets

  {
    "presets": {
      "web_standard": {
        "maxWidth": 1920,
        "format": "webp",
        "quality": 85,
        "enhancements": [
          "noise_reduction",
          "auto_levels_curves"
        ]
      },
      "web_high_quality": {
        "maxWidth": 3840,
        "format": "webp",
        "quality": 90,
        "enhancements": [
          "noise_reduction",
          "auto_levels_curves",
          "texture_enhancement"
        ]
      },
      "thumbnail": {
        "maxWidth": 400,
        "format": "webp",
        "quality": 80,
        "enhancements": [
          "noise_reduction"
        ]
      }
    }
  }
  

🚀 Getting Started

📥 Installation

1. Clone the repository:

git clone https://github.com/splendasucks/webperfect-mcp-server.git
cd webperfect-mcp-server

2. Install dependencies:

npm install

3. Build the server:

npm run build

🤖 Usage with Claude

1. Add the server to your Claude MCP settings (typically in claude_desktop_config.json):

{
  "mcpServers": {
    "webperfect": {
      "command": "node",
      "args": [
        "/path/to/webperfect-mcp-server/build/index.js"
      ],
      "env": {}
    }
  }
}

2. Restart Claude to load the MCP server.

3. The server will be available through Claude’s MCP tools and resources:

// Process a batch of images
<use_mcp_tool>
<server_name>webperfect</server_name>
<tool_name>process_images</tool_name>
<arguments>
{
  "inputDir": "/path/to/input",
  "outputDir": "/path/to/output"
}
</arguments>
</use_mcp_tool>

// Access processing statistics
<access_mcp_resource>
<server_name>webperfect</server_name>
<uri>stats/summary</uri>
</access_mcp_resource>

📋 Requirements

• 📦 Node.js >= 16
• 🖼️ Sharp image processing library
• 🔌 Model Context Protocol SDK

📄 License

MIT © 2024 WebPerfect Contributors