PageSpeed MCP Server: Extending AI Assistant Capabilities through Web Performance Analysis

Overview: What is PageSpeed MCP Server?

The PageSpeed MCP Server is a Model Context Protocol (MCP) server that enhances the functionality of AI applications like Claude Desktop by integrating with Google's PageSpeed Insights API. This integration allows these applications to perform detailed performance analysis on websites, providing comprehensive metrics and recommendations for optimizing web page performance. By acting as a bridge between AI models and external tools, this MCP server offers advanced capabilities such as assessing website speed, accessibility, SEO, and more.

🔧 Core Features & MCP Capabilities

The PageSpeed MCP Server is designed to significantly enhance the operational scope of AI applications by extending their reach into web performance analysis. Key features include:

Performance Metrics Analysis

• First Contentful Paint (FCP): Measures how quickly content appears on the page.
• Largest Contentful Paint (LCP): Evaluates time to first significant paintable layout box in the viewport.
• Time to Interactive (TTI): Calculates when an interactive UI is usable by the user.
• Total Blocking Time (TBT): Tracks periods where a page's responsiveness degrades due to blocking JavaScript execution.
• Cumulative Layout Shift (CLS): Quantifies visual jitter from layout changes and rendering delays.
• Speed Index: Provides an overview of a web page’s load experience.
• Time to First Byte (TTFB): Indicates the delay before initial bytes can be rendered.

Best Practices Assessment

• HTTPS Usage: Ensuring secure connections for websites.
• JavaScript Error Monitoring: Identifying issues that could impact user experience.
• Browser Console Warnings: Alerting developers to potential problems in their code.
• Deprecated API Usage: Highlighting outdated methods and practices.
• Image Aspect Ratio Analysis: Optimizing image layout for better user interface design.
• Link Security Checks: Validating the security of external links.

SEO Analysis

• Meta Description Validation: Ensuring meta descriptions contain relevant keywords.
• Robots.txt Validation: Checking the presence of directives in robots.txt files to inform search engines about crawling restrictions.
• Structured Data Validation: Verifying implementation of structured data for improved search visibility.
• Crawlable Links Verification: Ensuring all content is accessible and indexable by search crawlers.
• Meta Tags Assessment: Evaluating the effectiveness of meta tags on pages.
• Mobile Friendliness: Assessing whether a website is optimized for mobile devices.

Accessibility Audits

• ARIA Attribute Validation: Verifying accessibility-related attributes to ensure screen reader support.
• Color Contrast Checking: Ensuring sufficient contrast ratios meet WCAG guidelines.
• Heading Hierarchy Analysis: Ensuring headings are structured correctly and semantically meaningful.
• Alt Text Verification: Validating the use of text alternatives for images.
• Focus Management Assessment: Evaluating how focus is handled in interactive elements.
• Keyboard Navigation Testing: Assessing whether the website can be used effectively with only a keyboard.

Resource Optimization

• Image Optimization Suggestions: Recommending optimizations to improve image quality and reduce file sizes.
• JavaScript Bundling Analysis: Suggesting improvements for bundling scripts to enhance performance.
• CSS Optimization Recommendations: Providing tips for optimizing CSS files.
• Cache Policy Validation: Checking cache settings to ensure maximum utilization.
• Resource Minification Checks: Suggesting ways to minimize resource sizes without losing functionality.
• Render-Blocking Resource Identification: Identifying and managing resources that delay page load.

⚙️ MCP Architecture & Protocol Implementation

The PageSpeed MCP Server operates on the Model Context Protocol (MCP), which standardizes communication between AI applications and external tools. The protocol ensures seamless integration through a structured request-response framework, facilitating the efficient transfer of data without requiring changes to existing AI workflows.

Example of a Simple MCP Request-Response Flow

graph TD
    A[AI Application] -->|MCP Client| B[MCP Protocol]
    B --> C[MCP Server]
    C --> D[Data Source/Tool]
    style A fill:#e1f5fe
    style C fill:#f3e5f5
    style D fill:#e8f5e8

Example of Data Flow with Detailed Metrics

graph TD
    subgraph AI Application
        A[AI Model]
        B[Analysis Request (MCP)]
    end
    A -->|Through MCP| C[MCP Server]
    C --> D[PageSpeed Insights API Response]
    style C fill:#f3e5f5
    D --> E[Detailed Performance Data & Recommendations]
    E --> B[AI Application (Action/Notification Based on Results)]

🚀 Getting Started with Installation

Installing via Smithery

For quick and automated setup, you can install the PageSpeed MCP Server via Smithery for Claude Desktop using:

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

Manual Installation

Alternatively, manually install the server with:

npm install pagespeed-mcp-server

💡 Key Use Cases in AI Workflows

Real-Time Web Performance Analytics

Integration of PageSpeed MCP Server into Claude Desktop allows for immediate analysis of a website's performance. This is particularly useful for developers who need to quickly assess and optimize their web projects.

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

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

Continuous Monitoring & Optimization

For enterprise-level applications, continuous integration of performance metrics can be automated to ensure that website optimizations are consistently monitored and implemented.

async function monitorPerformance(url) {
    const results = await mcp.analyze(url, {
        strategy: 'mobile',
        categories: ['performance', 'accessibility'],
        locale: 'en-US'
    });
    
    console.log(results);
}

🔌 Integration with MCP Clients

The PageSpeed MCP Server is compatible with various MCP clients such as Claude Desktop, Continue, and Cursor. However, ensure that your AI application supports these integrations before proceeding.

MCP Client	Resources	Tools	Prompts	Status
Claude Desktop	✅	✅	✅	Full Support
Continue	✅	✅	✅	Full Support
Cursor	❌	✅	❌	Tools Only

📊 Performance & Compatibility Matrix

API Requirements & Specifications

• Stable Internet Connection: Required for constant and accurate performance data.
• Access to Google's PageSpeed Insights API

Platform Support

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

🛠️ Advanced Configuration & Security

Custom Configuration

For more advanced use cases, customize the analysis with 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 server includes robust error handling mechanisms for various issues:

• Invalid URLs
• Network Timeouts
• API Rate Limiting
• Invalid Parameters
• Server-Side Errors

❓ Frequently Asked Questions (FAQ)

1. What is the difference between FCP and LCP?

   • First Contentful Paint refers to when any text, image, or other content appears on the page. Largest Contentful Paint measures the paint time for the largest renderable element in the viewport.

2. How does the server handle rate limiting from Google's API?

   • The server includes built-in rate-limiting mechanisms and supports using an API key to increase allowable request limits.

3. Does the server support mobile-first strategies?

   • Yes, by setting the strategy parameter to 'mobile', you can analyze websites with a focus on ensuring good mobile performance.

4. Can I customize which categories of analysis are performed?

   • Absolutely, you can specify an array of categories such as ['performance', 'accessibility'] in your API request.

5. What if the website URL is invalid or not accessible?

   • The server will return appropriate error messages and status codes to handle these scenarios gracefully.

👨‍💻 Development & Contribution Guidelines

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.

🌐 MCP Ecosystem & Resources

Community & Support

• GitHub Issues: Report bugs and request features.

Additional Resources

• Model Context Protocol Documentation
• Google PageSpeed Insights API Documentation
• Examples of Advanced Use Cases

License

MIT License - See LICENSE file for details.

This document serves as an extensive guide to understanding and utilizing the PageSpeed MCP Server, positioning it as a critical tool for enhancing AI applications through integrated web performance analysis. By leveraging its capabilities, users can achieve more efficient, responsive, and user-friendly web experiences across various platforms and devices.