WebPerfect MCP Server

WebPerfect MCP Server

An intelligent MCP server with a fully automated batch pipeline for web-ready images. Features include noise reduction, auto levels/curves, JPEG artifact removal, 4K resizing, smart sharpening with shadow/highlight enhancement, and advanced WebP conversion. Optimized compression delivers smaller files without sacrificing quality.

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

Process and optimize a batch of images with advanced enhancements.

{
  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"]
      }
    }
  }
  

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