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

Strong noise reduction using median filtering
Intelligent auto levels and curves based on image entropy
Advanced texture enhancement with modulation and sharpening
Smart resolution optimization (up to 4K)
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

Clone the repository:

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

Install dependencies:

npm install

Build the server:

npm run build

Usage with Claude

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": {}
    }
  }
}

Restart Claude to load the MCP server.
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

Deploy Server

HTTP connection URL

security – no known vulnerabilities

license - permissive license

quality - confirmed to work

How are these scores calculated?

local-only server

The server can only run on the client's local machine because it depends on local resources.

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