@enemyrr/mcp-server-pagespeed

[MCP Server Name] MCP Server: Real-time Webpage Performance Analysis Through Model Context Protocol

Overview: What is @enemyrr/mcp-server-pagespeed MCP Server?

The @enemyrr/mcp-server-pagespeed MCP server provides real-time performance analysis for webpages using Google PageSpeed Insights API. It integrates seamlessly with AI applications like Claude Desktop, Continue, Cursor, and others through the Model Context Protocol (MCP), allowing them to leverage specialized tools and data sources in a standardized manner. This server enhances AI application capabilities by offering detailed loading experience metrics and prioritized improvement suggestions.

🔧 Core Features & MCP Capabilities

The @enemyrr/mcp-server-pagespeed server is designed with several core features that enhance its usability and integration with MCP clients:

• Real-time PageSpeed Analysis: The server integrates Google PageSpeed Insights API to provide instant performance scores and detailed metrics.

• Detailed Metrics: It offers first contentful paint (FCP) and first input delay (FID), which are crucial for evaluating webpage loading speed and user experience.

• Improvement Suggestions: Top 5 prioritized suggestions with actionable details enable developers to optimize websites effectively.

• Comprehensive Error Handling: Built-in error messages help in troubleshooting issues related to invalid URLs, API request failures, connection drops, or incorrect tool calls.

• TypeScript Support: The server supports TypeScript, ensuring robust and maintainable code development for AI applications.

⚙️ MCP Architecture & Protocol Implementation

The architecture of the @enemyrr/mcp-server-pagespeed conforms to the Model Context Protocol (MCP), ensuring seamless integration with various AI clients:

1. MCP Client Compatibility: The server is compatible with popular AI clients such as Claude Desktop, Continue, and Cursor. Each client has been evaluated for full support or tools-only compatibility.

2. MCP Protocol Flow: The protocol involves an MCP client initiating a request to the @enemyrr/mcp-server-pagespeed server, which then processes the request and returns detailed performance analysis.

3. Data Architecture: The server's internal data architecture is designed to efficiently handle API requests and return standardized responses according to the MCP specification.

🚀 Getting Started with Installation

To begin using the @enemyrr/mcp-server-pagespeed MCP server, follow these steps:

1. Clone and build the project:

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

2. Add the server in Cursor IDE settings:

   • Open Command Palette (Cmd/Ctrl + Shift + P)
   • Search for "MCP: Add Server"
   • Fill in the fields with the following details:
     • Name: pagespeed
     • Type: command
     • Command: node /absolute/path/to/mcp-server-pagespeed/build/index.js

💡 Key Use Cases in AI Workflows

Use Case 1: Webpage Performance Optimization for E-commerce Websites

Developers can use the @enemyrr/mcp-server-pagespeed MCP server to automatically analyze and optimize e-commerce websites. By integrating this server into an AI application, developers can proactively monitor and improve site performance using real-time PageSpeed insights.

Implementation:

use_mcp_tool({
  server_name: "pagespeed",
  tool_name: "analyze_pagespeed",
  arguments: {
    url: "https://example.com"
  }
});

Use Case 2: Performance Audits in Large-Scale Web Infrastructure Projects

Team leaders can leverage the @enemyrr/mcp-server-pagespeed MCP server to conduct comprehensive performance audits across multiple websites. This allows for efficient management of large-scale projects and ensures consistent quality.

🔌 Integration with MCP Clients

The @enemyrr/mcp-server-pagespeed MCP server supports integration with several popular MCP clients:

• Claude Desktop: Full support for all features.
• Continue: Full support for all features.
• Cursor: Tools-only compatibility, meaning it can be used to analyze webpages but does not provide full client functionality.

📊 Performance & Compatibility Matrix

The following table outlines the compatibility matrix for different MCP clients:

MCP Client	Resources	Tools	Prompts
Claude Desktop	✅	✅	✅
Continue	✅	✅	✅
Cursor	❌	✅	❌

🛠️ Advanced Configuration & Security

For advanced configurations and security settings, developers can modify the MCP server’s configuration file to include specific parameters such as API keys:

{
  "mcpServers": {
    "[server-name]": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-[name]"],
      "env": {
        "API_KEY": "your-api-key"
      }
    }
  }
}

❓ Frequently Asked Questions (FAQ)

1. How does the @enemyrr/mcp-server-pagespeed MCP server handle invalid URLs?

   • The server returns detailed error messages, including information about the invalid URL and recommended steps to correct it.

2. What kind of metrics are provided in the performance analysis?

   • Metrics include overall performance score (0-100), loading experience scores like FCP and FID, and top 5 improvement suggestions with actionable details.

3. Can this server be used with other AI applications besides those listed?

   • While primarily tested with specific clients, the server can be adapted for use with other MCP-compliant tools.

4. Are there any security concerns when using this server?

   • Yes, developers must ensure proper configuration of environment variables such as API keys to prevent unauthorized access and data breaches.

5. How often does the analysis update?

   • The server provides real-time updates based on requests from MCP clients, ensuring up-to-date performance metrics without delay.

👨‍💻 Development & Contribution Guidelines

Contributions are welcome! To contribute to the project:

1. Fork the repository.
2. Create a new branch for your development work.
3. Add, modify, or delete code as needed.
4. Ensure that all tests pass and updates meet compatibility standards.
5. Submit a pull request with detailed descriptions of changes.

🌐 MCP Ecosystem & Resources

For more information on the Model Context Protocol (MCP) and related resources, visit:

• MCP Documentation: https://modelcontextprotocol.org
• Community Forum: https://community.modelcontextprotocol.org

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This comprehensive documentation highlights the capabilities, integration with AI applications, configuration details, and best practices for using the @enemyrr/mcp-server-pagespeed MCP server. By following these guidelines, developers can effectively enhance their AI workflows through real-time web performance analysis.