@enemyrr/mcp-server-pagespeed

Name: @enemyrr/mcp-server-pagespeed
Author: MCP-Mirror

@MCP-Mirror

リポジトリ

@enemyrr/mcp-server-pagespeed について

Mirror of

#mcp-server #pagespeed #performance-analysis

基本情報

カテゴリ

その他

トランスポート

stdio

公開者

MCP-Mirror

設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "enemyrr_mcp-server-pagespeed": {
      "command": "npx",
      "args": [
        "mcp-server-pagespeed"
      ]
    }
  }
}

ツール

ツールは検出されませんでした

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is @enemyrr/mcp-server-pagespeed?

An MCP server that integrates Google PageSpeed Insights to let AI models analyze webpage performance and receive optimization suggestions through a standardized interface.

How to use @enemyrr/mcp-server-pagespeed?

Install by cloning the repository, running npm install and npm run build, then configure in Cursor IDE with the command node /absolute/path/to/build/index.js. Alternatively, run npx mcp-server-pagespeed directly from the command line. Use the analyze_pagespeed tool with a URL argument to obtain performance data.

Key features of @enemyrr/mcp-server-pagespeed

Real-time webpage performance analysis
Detailed loading experience metrics (FCP, FID)
Top 5 prioritized improvement suggestions
Comprehensive error handling for malformed URLs and API failures
Written in TypeScript with full type support

Use cases of @enemyrr/mcp-server-pagespeed

Automatically audit web page performance during development workflows
Generate actionable optimization recommendations from AI assistants
Integrate performance scoring into CI/CD or content review pipelines
Provide users with instant page speed insights via chat interfaces

FAQ from @enemyrr/mcp-server-pagespeed

How do I install and configure @enemyrr/mcp-server-pagespeed?

Clone the repository, run npm install and npm run build, then add it as an MCP server in Cursor IDE using the command node /absolute/path/to/build/index.js, or run npx mcp-server-pagespeed directly.

What tools does the server provide?

It provides one tool: analyze_pagespeed. It accepts a url argument and returns performance scores, loading metrics, and improvement suggestions.

What data does the analysis return?

The analysis returns an overall performance score (0–100), First Contentful Paint, First Input Delay, and the top five improvement suggestions, each with a title, description, potential impact, and current value.