MCP Server Pagespeed
@enemyrr/mcp-server-pagespeed
Un servidor de Protocolo de Contexto de Modelo que proporciona análisis de Google PageSpeed Insights. Este servidor permite que los modelos de IA analicen el rendimiento de las páginas web mediante una interfaz estandarizada.
Instalación y configuración de Cursor IDE
Clonar y construir el proyecto:
git clone https://github.com/enemyrr/mcp-server-pagespeed.git
cd mcp-server-pagespeed
npm install
npm run buildAgregue el servidor en la configuración de Cursor IDE:
Abrir la paleta de comandos (Cmd/Ctrl + Shift + P)
Buscar "MCP: Agregar servidor"
Rellene los campos:
Nombre:
pagespeedTipo:
commandComando:
node /absolute/path/to/mcp-server-pagespeed/build/index.js
Nota : Reemplace
/absolute/path/to/con la ruta real donde clonó y construyó el proyecto.
Related MCP server: Lighthouse MCP
Uso de la línea de comandos
Simplemente ejecuta:
npx mcp-server-pagespeedHerramientas disponibles
analizar_velocidad_de_página
Analice una página web mediante la API de Google PageSpeed Insights.
use_mcp_tool({
server_name: "pagespeed",
tool_name: "analyze_pagespeed",
arguments: {
url: "https://example.com"
}
});La herramienta devuelve:
Puntuación de rendimiento general (0-100)
Métricas de la experiencia de carga
Primera pintura con contenido
Retardo de la primera entrada
Las 5 mejores sugerencias de mejora con:
Título
Descripción
Impacto potencial
Valor actual
Características
Análisis del rendimiento de páginas web en tiempo real
Métricas detalladas de la experiencia de carga
Sugerencias de mejora priorizadas
Manejo integral de errores
Compatibilidad con TypeScript
Manejo de errores
El servidor proporciona mensajes de error detallados para:
URL no válidas
Errores en las solicitudes de API
Problemas de conexión
Llamadas de herramientas no válidas
Contribuyendo
¡Agradecemos sus contribuciones! No dude en enviar una solicitud de extracción a https://github.com/enemyrr/mcp-server-pagespeed
Licencia
Instituto Tecnológico de Massachusetts (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.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
1 tool update
- First observed
analyze_pagespeed
TDQS
Scored across 1 tool
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
Related MCP Connectors
- gtmetrixOAuthcom.gtmetrix
Analyze web performance and get optimization insights from GTmetrix, directly in your AI workflow.
SEO & marketing toolkit for AI agents: GA4, Search Console, AdSense, GTM, PageSpeed, Trends.
Google PageSpeed Insights — runs Lighthouse against any public URL and returns the performance…
Audit any site's AI visibility from your assistant: crawler access, rendering, and schema.
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