Herramienta MCP para búsquedas en Google y extracción de contenido de páginas web mediante el navegador Chrome. Funciona con Claude para habilitar las funciones de búsqueda y obtención de contenido de Google.
Configurar Claude Desktop
Abra Claude Desktop en Mac
Vaya a Claude > Configuración > Desarrollador > Editar configuración
Agregue lo siguiente a su archivo de configuración: GXP1
Reiniciar Claude Desktop
Configuración por primera vez
Otorgar permisos de accesibilidad
En la primera ejecución, apruebe la solicitud de permisos de accesibilidad de macOS
Vaya a: Preferencias del Sistema > Seguridad y Privacidad > Privacidad > Accesibilidad
Agregue y habilite permisos para su aplicación de terminal
Habilitar JavaScript de Chrome desde Apple Events
Abrir Chrome
Vaya a: Ver > Desarrollador > Permitir JavaScript desde Apple Events
Configuración única únicamente
Una vez configurado, Claude podrá realizar búsquedas en Google y extraer contenido de páginas web a través de Chrome cuando realices solicitudes.
Related MCP server: Google Search MCP
Búsqueda gratuita en Google
Abre ventanas pequeñas y utiliza su navegador Chrome, por lo que no debería bloquearse.
Dado que usa tu ventana de Chrome, puede acceder a contenido autenticado. Claude puede simplemente abrir la URL en tu navegador.
✅ macOS
❌ Windows (no compatible)
❌ Linux (no compatible)
macOS
Google Chrome
Node.js 20 o superior
npx mcp-chrome-google-searchObtener desde git
Ejecutar npm run build
Agregar a la configuración de Claude (usar ruta absoluta):
{
"google-tools": {
"command": "node",
"args": [
"/your/checkout/path/mcp/mcp-chrome-google-search/dist/index.js"
]
}
}Para probar los cambios localmente, aumente la versión del paquete json y ejecútelo para ponerlo en modo de edición:
npm install -g .Luego simplemente haga npm run build y los archivos irán a dist donde Claude está monitoreando
Luego presione ctrl-R en el escritorio de Claude, no es necesario reiniciarlo.
# Follow logs in real-time
tail -n 20 -F ~/Library/Logs/Claude/mcp*.logHabilitar la configuración del desarrollador:
echo '{"allowDevTools": true}' > ~/Library/Application\ Support/Claude/developer_settings.jsonAbrir DevTools: Comando-Opción-Mayús-i en el escritorio de Claude
Utilice Ctrl+R en el escritorio de Claude mientras rastrea errores para obtener mejores resultados
Si ves:
execution error: Google Chrome got an error: Executing JavaScript through AppleScript
is turned off. For more information: https://support.google.com/chrome/?p=applescript (12)Solución:
Abrir Chrome
Ver > Desarrollador > Permitir JavaScript desde Apple Events
Si el control de Chrome falla:
Abrir Preferencias del Sistema
Seguridad y privacidad > Privacidad > Accesibilidad
Asegúrese de que la aplicación de terminal esté listada y habilitada
Utilice el icono del candado para realizar cambios si es necesario
Utiliza AppleScript para el control de Chrome
Automatización visible: las ventanas de Chrome se abrirán/navegarán
Cada solicitud abre una nueva pestaña de Chrome
Cierre periódicamente las pestañas no utilizadas para un rendimiento óptimo
Usar solo con instancias confiables de Claude (que tengan acceso al control de Chrome)
Crear problemas en GitHub para los problemas
Incluir detalles de la versión de macOS y Chrome
Licencia MIT: consulte el archivo de LICENCIA para obtener más detalles
Extract readable text content from a webpage using Chrome browser automation.
Key Features:
Returns main content text and optionally links
| Name | Required | Description | Default |
|---|---|---|---|
| includeLinks | No | Whether to include extracted links in the output | |
| url | Yes | Webpage URL to fetch (must include http:// or https://) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions Chrome browser automation and returning main content text with optional links, but lacks critical behavioral details: it doesn't specify if this is a read-only operation, potential rate limits, authentication needs, error handling for inaccessible pages, or what 'readable text' entails (e.g., stripping HTML, handling dynamic content). The description adds some context but leaves significant gaps for a tool interacting with external webpages.
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 concise and well-structured with a clear opening sentence followed by a bullet point. Every sentence earns its place by stating the core purpose and a key feature. However, the bullet point format is slightly redundant with the main sentence, and it could be more front-loaded by integrating the optional links feature into the initial statement.
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 complexity of web scraping (external interactions, potential failures) and lack of annotations or output schema, the description is incomplete. It doesn't explain return values beyond 'main content text and optionally links', leaving the agent uncertain about output structure, error responses, or behavioral constraints like timeouts or permissions. For a tool with no structured safety hints, this is inadequate.
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?
Schema description coverage is 100%, with clear descriptions for both parameters in the schema itself. The description adds minimal value beyond the schema: it mentions 'optionally links' which aligns with the 'includeLinks' parameter but doesn't provide additional semantic context. With high schema coverage, the baseline is 3, and the description doesn't significantly enhance parameter understanding.
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: 'Extract readable text content from a webpage using Chrome browser automation.' It specifies the verb (extract), resource (text content from a webpage), and method (Chrome browser automation). However, it doesn't explicitly differentiate from its sibling 'web-search' tool, which likely searches rather than extracts content from a specific URL.
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. It mentions 'optionally links' as a feature but doesn't clarify scenarios where including links is beneficial or when to choose this over 'web-search'. There's no mention of prerequisites, limitations, or typical use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search webpages and get a specific page of results (each page has ~10 results). Optionally filter by site and timeframe.
| Name | Required | Description | Default |
|---|---|---|---|
| pageNumber | No | Which page of results to fetch (1-5). Each page contains ~10 results | |
| query_text | Yes | Plain text to search for (no Google operators plain text only - use other parameters for site/date filtering) | |
| site | No | Limit search to specific domain (e.g. 'github.com' or 'docs.python.org') | |
| timeframe | No | Time range filter (h=hour, d=day, w=week, m=month, y=year) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It adds some context beyond basic functionality: it mentions pagination ('each page has ~10 results') and optional filtering capabilities. However, it doesn't cover important aspects like rate limits, authentication needs, error handling, or what the output looks like (e.g., result format), which are significant gaps for a search tool.
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 extremely concise and front-loaded: it states the core purpose in the first clause and adds key details in a second sentence. Every word earns its place, with no redundancy or fluff, making it highly efficient for quick understanding.
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 tool's moderate complexity (4 parameters, no output schema, no annotations), the description is somewhat complete but has gaps. It covers the basic operation and filtering options but lacks details on output format, error cases, or integration with the sibling tool. Without annotations or output schema, more behavioral context would be beneficial for full completeness.
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?
Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds minimal value beyond the schema by hinting at the optional nature of site and timeframe filters, but it doesn't provide additional semantic context or usage examples. This meets the baseline for high schema coverage.
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: 'Search webpages and get a specific page of results.' It specifies the verb ('search') and resource ('webpages'), and distinguishes it from the sibling tool 'web_fetch' by implying this is for search results rather than fetching specific pages. However, it doesn't explicitly contrast with the sibling, keeping it from a perfect score.
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 implied usage context by mentioning optional filters ('Optionally filter by site and timeframe'), which suggests when to use these parameters. However, it lacks explicit guidance on when to choose this tool over the sibling 'web_fetch' or any other alternatives, and doesn't specify prerequisites or exclusions, leaving room for ambiguity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
v1.0.0web_fetchweb-searchScored across 2 tools
The two tools have clearly distinct purposes: web_fetch extracts content from a specific webpage, while web_search performs web searches and returns result pages. There is no overlap in functionality, making it easy for an agent to choose the correct tool based on the task.
Both tool names follow a consistent snake_case pattern with a clear verb-noun structure: web_fetch and web_search. The naming is predictable and readable, with no deviations in style or convention.
With only 2 tools, the server feels thin for a Google Search domain, which typically involves more operations like advanced filtering, image search, or history management. While the tools cover basic fetch and search, the scope is limited and could benefit from additional functionality to fully represent the domain.
The tools cover core search and content extraction, but there are notable gaps for a Google Search server, such as no tools for image search, news search, or handling search settings. Agents can perform basic tasks but may encounter dead ends for more advanced operations, indicating incomplete coverage of the domain.
Google search, news, maps, scholar and public webpages for AI agents, with Markdown results.
Real Chrome for agents: start a browser, read pages as numbered markdown, click, type, hand off.
Web search, browser automation, scraping, crawling and CAPTCHA solving for AI agents.
Web search and page-reading for AI agents. One-click OAuth connect, or a Caesar API key.
