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ChanMeng666

Google Jobs MCP Server

by ChanMeng666

Una implementación de servidor del Protocolo de Contexto de Modelo (MCP) que proporciona funciones de búsqueda de Google Jobs mediante la integración con SerpAPI. Ofrece compatibilidad con varios idiomas, parámetros de búsqueda flexibles y gestión inteligente de errores.

Pregúntale a DeepWiki

¡Pruébalo ahora!

https://github.com/user-attachments/assets/8f6739e1-7db7-4171-88b4-59c6290a4c72

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✨ Características

🌍 Soporte multilingüe

Soporte de localización completo para inglés, chino, japonés y coreano con detección y recuperación automática del idioma.

🔍 Opciones de búsqueda flexibles

Parámetros de búsqueda completos que incluyen:

  • Título del puesto y palabras clave

  • Ubicación con filtrado de radio

  • Tipo de empleo (tiempo completo, tiempo parcial, etc.)

  • Filtros de rango salarial

  • Filtrado de fecha de publicación

  • Ordenación de resultados

💡 Manejo inteligente de errores

  • Validación de entrada integral

  • Mensajes de error y sugerencias útiles

  • Sugerencias automáticas de refinamiento de búsqueda

  • Manejo del límite de velocidad

📊 Detalles del trabajo enriquecidos

  • Formato detallado de la información del trabajo

  • Beneficios y aspectos destacados de la empresa

  • Información salarial cuando esté disponible

  • Enlaces directos de aplicaciones

  • Marcas de tiempo de publicación de empleo

🔄 Funciones avanzadas

  • Soporte de paginación

  • Múltiples opciones de clasificación

  • Búsqueda por radio geográfico

  • Filtrado por tipo de empleo

Guía de configuración de la API SERP

Antes de comenzar, necesitará obtener una clave API SERP:

  1. Visita el sitio web de SERP API y crea una cuenta

  2. Después de registrarse, vaya a su Panel de Control:

    • Localice la sección "Clave API"

    • Copia tu clave API

    • Los nuevos usuarios obtienen 100 llamadas API gratuitas

  3. Detalles de uso de la API:

    • Nivel gratuito: 100 búsquedas por mes

    • Los planes pagos comienzan en $50/mes por 5000 búsquedas

    • Facturación basada en llamadas API exitosas

    • Múltiples métodos de pago: Tarjeta de crédito, PayPal, etc.

  4. Límites de uso:

    • Tasa de solicitud: 2 solicitudes/segundo

    • Restricciones de IP: Ninguna

    • Solicitudes concurrentes: 5

    • Tiempo de caché de respuesta: 1 hora

👩‍🔧 Solución para problemas de conexión de servidores MCP con NVM/NPM

Haga clic para ver mi solución de configuración 👉 https://github.com/modelcontextprotocol/servers/issues/76

🚀 Inicio rápido

  1. Instalar dependencias:

npm install
  1. Configurar el entorno: Modifique su claude_desktop_config.json con el siguiente contenido (ajuste las rutas según su sistema):

{
  "google-jobs": {
    "command": "D:\\Program\\nvm\\node.exe",
    "args": ["D:\\github_repository\\path_to\\dist\\index.js"],
    "env": {
      "SERP_API_KEY": "your-api-key"
    }
  }
}
  1. Construir el servidor:

npm run build
  1. Iniciar el servidor:

npm start

Solución de problemas

  1. Problemas con la clave API:

  • Verificar clave en configuración

  • Comprobar el estado de la clave en el panel de la API de SERP

  • Confirmar que la clave tiene cuota restante

  1. Problemas de búsqueda:

  • Validar el formato de los parámetros de búsqueda

  • Comprobar la conectividad de la red

  • Verificar la compatibilidad del código de país/idioma

📦 Instalación

Related MCP server: Scrapeless MCP Server

Instalación mediante herrería

Para instalar Google Jobs para Claude Desktop automáticamente a través de Smithery :

npx -y @smithery/cli install @chanmeng666/google-jobs-server --client claude

Instalación manual

@chanmeng666/servidor de empleos de Google

# Using npm
npm i @chanmeng666/google-jobs-server
# or
npm install @chanmeng666/google-jobs-server

# Using yarn
yarn add @chanmeng666/google-jobs-server

# Using pnpm
pnpm add @chanmeng666/google-jobs-server

Ejecución de evaluaciones

El paquete evals carga un cliente mcp que ejecuta el archivo index.ts, por lo que no es necesario reconstruir entre pruebas. Puede cargar variables de entorno prefijando el comando npx. Puede encontrar la documentación completa aquí .

OPENAI_API_KEY=your-key  npx mcp-eval src/evals/evals.ts src/index.ts

Pila tecnológica

MecanografiadoNodeJSMCP

📖 Documentación de la API

El servidor implementa el Protocolo de Contexto de Modelo y expone una herramienta de búsqueda de empleo con los siguientes parámetros:

  • query : cadena de consulta de búsqueda (obligatoria)

  • location : Lugar de trabajo (opcional)

  • posted_age : Filtro de fecha de publicación (opcional)

  • employment_type : Filtro de tipo de trabajo (opcional)

  • salary : Filtro de rango salarial (opcional)

  • radius : Radio de búsqueda geográfica (opcional)

  • hl : Código de idioma (opcional)

  • page : Número de paginación (opcional)

  • sort_by : Orden de clasificación (opcional)

🔧 Desarrollo

# Run in development mode
npm run dev

# Run type checking
npm run typecheck

# Build for production
npm run build

📝 Licencia

Este proyecto tiene licencia MIT .

🙋‍♀ Autor

Creado y mantenido por Chan Meng . GitHub LinkedIn

Available Tools

1 tool
search_jobsB

Google Jobs API search tool.

Supported search parameters:

  1. Basic Search: Job title or keywords

  2. Location: City or region

  3. Time Filter: Recently posted jobs

  4. Job Type: Full-time, part-time, contract, internship

  5. Salary Range: Filter by compensation

  6. Geographic Range: Set search radius

  7. Language: Multi-language support

All parameters except 'query' are optional and can be freely combined.

ParametersJSON Schema
NameRequiredDescriptionDefault
queryYesSearch keywords (Required, e.g., 'software engineer', 'data analyst', 'product manager')
locationNoJob location (Optional, e.g., 'New York', 'London', 'Tokyo')
posted_ageNoPosting date filter (Optional) Options: - "today": Posted today - "3days": Last 3 days - "week": Last week - "month": Last month
employment_typeNoJob type (Optional) Options: - "FULLTIME": Full-time - "PARTTIME": Part-time - "CONTRACTOR": Contractor - "INTERN": Internship - "TEMPORARY": Temporary
salaryNoSalary range (Optional) Format examples: - "$50K+": Above $50,000 - "$100K+": Above $100,000 - "$150K+": Above $150,000
radiusNoSearch radius (Optional) Format examples: - "10mi": Within 10 miles - "20mi": Within 20 miles - "50mi": Within 50 miles
hlNoResult language (Optional) Options: - "en": English - "zh-CN": Chinese - "ja": Japanese - "ko": Koreanen
pageNoPage number (Optional, default: 1) - 10 results per page - Supports pagination
sort_byNoSort order (Optional) Options: - "date": Sort by date - "relevance": Sort by relevance - "salary": Sort by salaryrelevance

TDQS

B3.2/5.0
Behavior2/5

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 describes the search parameters and their optionality, which is useful, but it doesn't mention rate limits, authentication requirements, error handling, or what the output looks like (e.g., format, pagination details beyond '10 results per page' in the schema). For a tool with 9 parameters and no annotations, this leaves significant gaps in understanding its behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately sized and front-loaded, starting with the tool's purpose and followed by a structured list of parameters. Every sentence adds value, with no redundant information. However, the bulleted list could be slightly more concise, and the final sentence about optional parameters is necessary but adds length.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (9 parameters, no output schema, no annotations), the description is partially complete. It covers the search parameters well but lacks details on behavioral aspects like rate limits, authentication, and output format. Without annotations or an output schema, the description should do more to compensate, but it provides a functional overview that is adequate for basic use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 100%, meaning all parameters are well-documented in the input schema itself. The description adds value by summarizing the supported search parameters in a bulleted list and noting their optionality, but it doesn't provide additional semantic context beyond what the schema already covers (e.g., no examples of combined usage). 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.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool searches for jobs using the Google Jobs API with specific search parameters. It provides a verb ('search') and resource ('jobs'), making the purpose immediately understandable. However, since there are no sibling tools mentioned, it doesn't need to differentiate from alternatives, so a 5 is not warranted.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage through the list of supported search parameters and notes that all parameters except 'query' are optional. This provides some context for when to use certain features, but it doesn't offer explicit guidance on when to use this tool versus alternatives (none mentioned) or any prerequisites. The guidance is functional but not strategic.

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. 1 tool updatev1.0.0
    • First observedsearch_jobs

TDQS

B3.3/5.0

Scored across 1 tool

Disambiguation5/5

With only one tool, there is no possibility of ambiguity or overlap between tools. The single tool 'search_jobs' has a clearly defined and distinct purpose for job searching.

Naming Consistency5/5

The tool name 'search_jobs' follows a consistent verb_noun pattern. Since there is only one tool, there is no inconsistency to evaluate, and the naming is straightforward and descriptive.

Tool Count2/5

A single tool is too few for a server named 'Google Jobs MCP Server', which implies a broader domain of job-related operations. While search is a core function, the lack of tools for actions like retrieving job details, applying, or managing saved jobs makes the set feel incomplete and thin.

Completeness2/5

The tool surface is severely incomplete for a jobs domain. It only provides search functionality, missing essential operations such as getting detailed job information, applying to jobs, saving or bookmarking jobs, or filtering by employer. This will likely cause agent failures when trying to perform common job-related tasks beyond basic searching.

Maintenance

ActivityInactive
ResponsivenessNo issues

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