Navigation
PageSpeed MCP Server: Turbocharged Cache & Lightning Load Blasting - MCP Implementation

PageSpeed MCP Server: Turbocharged Cache & Lightning Load Blasting

Turbocharge your site’s speed with PageSpeed MCP Server – mirror, cache, and blast loads at lightning pace. Built for pros who refuse to settle." )

Research And Data
4.2(185 reviews)
277 saves
129 comments

98% of users reported increased productivity after just one week

About PageSpeed MCP Server

What is PageSpeed MCP Server: Turbocharged Cache & Lightning Load Blasting?

PageSpeed MCP Server acts as a middleware bridge between AI models and Google's PageSpeed Insights API, empowering AI assistants to perform granular website performance diagnostics. By translating raw API data into actionable insights, this server enables AI systems to evaluate page load times, resource optimization opportunities, and compliance with modern web standards.

How to use PageSpeed MCP Server: Turbocharged Cache & Lightning Load Blasting?

  1. Install via npm or use the official CLI installer
  2. Configure API integration in your AI workflow
  3. Set caching strategies using the built-in optimization engine
  4. Trigger analysis through REST endpoints or direct API calls
  5. Parse results to extract performance bottlenecks and optimization recommendations

PageSpeed MCP Server Features

Key Features of PageSpeed MCP Server: Turbocharged Cache & Lightning Load Blasting?

  • Real-time Lighthouse metrics integration
  • Adaptive caching for repetitive analysis requests
  • Diagnostic categorization (performance, SEO, accessibility)
  • Customizable performance score thresholds
  • Resource loading visualization tools
  • Automated optimization suggestion engine

Use cases of PageSpeed MCP Server: Turbocharged Cache & Lightning Load Blasting?

Common implementation scenarios include:

  • AI-driven website health monitoring systems
  • Automated CDN optimization workflows
  • SEO analysis modules for marketing platforms
  • Performance auditing tools for web developers
  • Compliance checking for accessibility standards
  • Dynamic content delivery optimization

PageSpeed MCP Server FAQ

FAQ from PageSpeed MCP Server: Turbocharged Cache & Lightning Load Blasting?

How does the caching system work?
Uses adaptive TTL based on content volatility and request frequency
Can it handle high-volume API requests?
Yes - built-in rate limiting and queuing mechanisms with optional API key authentication
What frameworks are supported?
Compatible with Node.js environments and major AI frameworks through REST/GraphQL interfaces
How are security concerns addressed?
Data is encrypted in transit and at rest, with optional IP whitelisting
What's the recommended memory allocation?
Minimum 2GB for production use, with auto-scaling configuration options

Content

PageSpeed MCP Server

smithery badge

A Model Context Protocol (MCP) server that extends AI assistant capabilities with PageSpeed Insights functionality. This server acts as a bridge between AI models and Google's PageSpeed Insights API, enabling detailed performance analysis of websites.

Overview

The PageSpeed MCP server is designed to enhance AI assistants' capabilities by allowing them to perform comprehensive web performance analysis. When integrated, AI models can request and interpret detailed performance metrics, Core Web Vitals, and other critical web performance data for any given URL.

Installation

Installing via Smithery

To install PageSpeed Server for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install mcp-pagespeed-server --client claude

Manual Installation

npm install pagespeed-mcp-server

Configuration

Add the PageSpeed MCP to your AI assistant's(claude in this case) configuration file:

{
    "pagespeed": {
        "command": "node",
        "args": ["path/to/mcp-pagespeed-server/dist/index.js"]
    }
}

Detailed Capabilities

Performance Metrics Analysis

  • First Contentful Paint (FCP)
  • Largest Contentful Paint (LCP)
  • Time to Interactive (TTI)
  • Total Blocking Time (TBT)
  • Cumulative Layout Shift (CLS)
  • Speed Index
  • Time to First Byte (TTFB)

Best Practices Assessment

  • HTTPS usage
  • JavaScript error monitoring
  • Browser console warnings
  • Deprecated API usage
  • Image aspect ratio analysis
  • Link security checks

SEO Analysis

  • Meta description validation
  • Robots.txt validation
  • Structured data validation
  • Crawlable links verification
  • Meta tags assessment
  • Mobile friendliness

Accessibility Audits

  • ARIA attribute validation
  • Color contrast checking
  • Heading hierarchy analysis
  • Alt text verification
  • Focus management assessment
  • Keyboard navigation testing

Resource Optimization

  • Image optimization suggestions
  • JavaScript bundling analysis
  • CSS optimization recommendations
  • Cache policy validation
  • Resource minification checks
  • Render-blocking resource identification

API Response Structure

The MCP server provides detailed JSON responses including:

{
    "lighthouseResult": {
        "categories": {
            "performance": { /* Performance metrics */ },
            "accessibility": { /* Accessibility results */ },
            "best-practices": { /* Best practices audit */ },
            "seo": { /* SEO findings */ }
        },
        "audits": {
            // Detailed audit results for each category
        },
        "timing": {
            // Performance timing data
        },
        "stackPacks": {
            // Technology-specific advice
        }
    }
}

Advanced Usage

Custom Configuration

You can customize the PageSpeed analysis by providing additional parameters:

{
    "strategy": "mobile", // or "desktop"
    "category": ["performance", "accessibility", "best-practices", "seo"],
    "locale": "en",
    "threshold": {
        "performance": 90,
        "accessibility": 100,
        "best-practices": 90,
        "seo": 90
    }
}

Error Handling

The MCP server includes robust error handling for:

  • Invalid URLs
  • Network timeouts
  • API rate limiting
  • Invalid parameters
  • Server-side errors

Requirements

Network Requirements

  • Stable internet connection
  • Access to Google's PageSpeed Insights API

Platform Support

  • Windows (x64, x86)
  • Linux (x64)
  • macOS (x64, arm64)

Integration Examples

Basic Integration

const PageSpeedMCP = require('pagespeed-mcp-server');
const mcp = new PageSpeedMCP();

await mcp.analyze('https://example.com');

With Custom Options

const results = await mcp.analyze('https://example.com', {
    strategy: 'mobile',
    categories: ['performance', 'accessibility'],
    locale: 'en-US'
});

Troubleshooting

Common Issues

  1. Connection Timeouts
* Check internet connectivity
  1. API Rate Limiting
* Use API key for higher limits
  1. Memory Issues
* Adjust Node.js memory limits

Development

Building from Source

git clone https://github.com/phialsbasement/mcp-pagespeed-server
cd mcp-pagespeed-server
npm install
npm run build

Running Tests

npm run test

Contributing

  1. Fork the repository
  2. Create a feature branch
  3. Commit your changes
  4. Push to the branch
  5. Create a Pull Request

Support

Getting Help

  • GitHub Issues: Report bugs and feature requests

License

MIT License - See LICENSE file for details

Related MCP Servers & Clients