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mcp-server-pagespeed

by enemyrr

A Model Context Protocol server that provides Google PageSpeed Insights analysis. This server enables AI models to analyze webpage performance through a standardized interface.

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What is mcp-server-pagespeed?

This is a Model Context Protocol (MCP) server that leverages the Google PageSpeed Insights API to analyze webpage performance. It provides a standardized interface for AI models to access and utilize webpage performance data.

How to use mcp-server-pagespeed?

The server can be used via command-line or integrated into the Cursor IDE. For Cursor IDE, clone the repository, build the project, and add the server in the IDE settings, specifying the path to the built index.js file. For command-line usage, simply run npx mcp-server-pagespeed. You can then use the analyze_pagespeed tool with a URL to analyze.

Key features of mcp-server-pagespeed

  • Real-time webpage performance analysis

  • Detailed loading experience metrics

  • Prioritized improvement suggestions

  • Comprehensive error handling

  • TypeScript support

Use cases of mcp-server-pagespeed

  • Automated webpage performance monitoring

  • Integration with AI models for optimization suggestions

  • Performance analysis within development environments

  • Identifying and prioritizing website improvements

  • Analyzing the impact of code changes on page speed

FAQ from mcp-server-pagespeed

What is Google PageSpeed Insights?

Google PageSpeed Insights is a tool that analyzes the speed and usability of your site on a variety of devices.

What metrics are provided by analyze_pagespeed tool?

The tool returns the overall performance score, loading experience metrics (First Contentful Paint, First Input Delay), and top 5 improvement suggestions with their title, description, potential impact, and current value.

What kind of errors does the server handle?

The server provides detailed error messages for invalid URLs, API request failures, connection issues, and invalid tool calls.

How can I contribute to this project?

Contributions are welcome! Please submit a Pull Request to the GitHub repository.

What is the license for this project?

This project is licensed under the MIT License.