MCP Server Pagespeed
With the MCP Server Pagespeed, you can analyze webpage performance using Google PageSpeed Insights.
Real-time performance analysis: Get instant insights into webpage loading metrics like First Contentful Paint and First Input Delay
Performance scoring: Receive an overall performance score (0-100)
Improvement suggestions: View the top 5 prioritized recommendations with title, description, potential impact, and current value
Error handling: Access detailed error messages for invalid URLs, API failures, and other issues
TypeScript support: Integrate the server seamlessly with TypeScript-based projects
Allows analyzing webpage performance using Google PageSpeed Insights API, providing performance scores, loading experience metrics, and improvement suggestions
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@MCP Server Pagespeedanalyze the performance of https://example.com"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
@enemyrr/mcp-server-pagespeed
A Model Context Protocol server that provides Google PageSpeed Insights analysis. This server enables AI models to analyze webpage performance through a standardized interface.
Installation & Setup for Cursor IDE
Clone and build the project:
git clone https://github.com/enemyrr/mcp-server-pagespeed.git
cd mcp-server-pagespeed
npm install
npm run buildAdd the server in Cursor IDE settings:
Open Command Palette (Cmd/Ctrl + Shift + P)
Search for "MCP: Add Server"
Fill in the fields:
Name:
pagespeedType:
commandCommand:
node /absolute/path/to/mcp-server-pagespeed/build/index.js
Note: Replace
/absolute/path/to/with the actual path where you cloned and built the project.
Related MCP server: Lighthouse MCP
Command-line Usage
Just run:
npx mcp-server-pagespeedAvailable Tools
analyze_pagespeed
Analyze a webpage using Google PageSpeed Insights API.
use_mcp_tool({
server_name: "pagespeed",
tool_name: "analyze_pagespeed",
arguments: {
url: "https://example.com"
}
});The tool returns:
Overall performance score (0-100)
Loading experience metrics
First Contentful Paint
First Input Delay
Top 5 improvement suggestions with:
Title
Description
Potential impact
Current value
Features
Real-time webpage performance analysis
Detailed loading experience metrics
Prioritized improvement suggestions
Comprehensive error handling
TypeScript support
Error Handling
The server provides detailed error messages for:
Invalid URLs
API request failures
Connection issues
Invalid tool calls
Contributing
Contributions are welcome! Please feel free to submit a Pull Request to https://github.com/enemyrr/mcp-server-pagespeed
License
MIT
Available Tools
1 toolanalyze_pagespeedC
Analyzes a webpage using Google PageSpeed Insights API
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | The URL to analyze |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the API but fails to describe key traits like rate limits, authentication needs, error handling, or what the analysis entails (e.g., performance metrics, recommendations). This leaves the agent with insufficient information about how the tool behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's function without unnecessary words. It is appropriately sized and front-loaded, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete. It does not explain what the analysis returns (e.g., scores, suggestions) or behavioral aspects like API constraints. For a tool that likely provides detailed performance data, this omission is significant, leaving the agent without enough context to understand the tool's full scope.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with the 'url' parameter documented as 'The URL to analyze.' The description does not add any meaning beyond this, such as URL format requirements or examples. With high schema coverage, the baseline score of 3 is appropriate, as the schema handles the parameter documentation adequately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Analyzes a webpage using Google PageSpeed Insights API.' It specifies the verb ('analyzes') and resource ('a webpage'), and mentions the underlying API. However, with no sibling tools, it cannot demonstrate differentiation from alternatives, preventing a perfect score of 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, prerequisites, or exclusions. It simply states what the tool does without context for its application, which is a significant gap in usage instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
TDQS
With only one tool, there is no possibility of confusion or overlap between tools. The tool's purpose is clearly defined and distinct by default.
The single tool name follows a clear verb_noun pattern (analyze_pagespeed). Since there is only one tool, consistency is inherently perfect with no deviations to assess.
A single tool is too few for a server named 'MCP Server Pagespeed', which suggests a broader scope for page speed analysis. This minimal set feels thin and limits functionality, as it only covers analysis without supporting operations like history tracking or batch processing.
The tool surface is severely incomplete for a page speed analysis domain. It only provides analysis but lacks essential operations such as retrieving historical results, comparing analyses, or managing configurations, leaving significant gaps for agent workflows.
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Connectors
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