PageSpeed MCP Server

PageSpeed MCP Server

Enables AI assistants to perform comprehensive web performance analysis using Google's PageSpeed Insights API, including metrics, best practices, SEO, and accessibility audits.

Category
Visit Server

README

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
  2. API Rate Limiting

    • Use API key for higher limits
  3. 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

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured