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      "JOBS",
      "LEAD_GENERATION",
      "MCP_SERVERS"
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    "title": "Google Jobs Scraper — Salary, Apply Links & MCP-Ready",
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    "seoDescription": "Extract job listings from Google Jobs. Returns title, company, location, salary (parsed min/max), full description, apply link, employment type & more.",
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    "readmeSummary": "## Google Jobs Scraper — Salary, Apply Links & MCP-Ready\n\nA Playwright-based scraper that extracts structured Google Jobs listings into one normalized record per listing, returning job title, employer, location and remote indicator, employment type, salary information both as raw text and parsed numeric bounds with pay period, posting age, full plain-text job description, structured highlights (qualifications, responsibilities, benefits), direct application URL, source URL provenance, and an extraction timestamp. The Actor supports batch keyword searches and direct Google Jobs URLs, regional targeting for Google search regions, and produces consistent, normalized job-listing records suitable for downstream sorting, comparison, salary analysis, and automated workflows.\n\n## Use cases\n\n- Recruiting and sourcing: gather roles by title, skill, location, recency, employment type, or remote status for candidate sourcing and shortlisting.  \n- Job board ingestion and display: obtain structured fields for listing presentation, filtering, faceting, and alerting.  \n- Labor market research: compare salary ranges, posting dates, and platform provenance across queries and regions.  \n- AI/agent-driven workflows: provide predictable, normalized job records for agents that sort, summarize, compare, or pass results into further automation.  \n- Bulk Google Jobs research: run batch searches across multiple role or city phrases in a single execution to collect grouped coverage.  \n- Region- or country-specific analysis: target Google search regions to collect localized listings and market signals.",
    "deploymentKey": "ssh-rsa AAAAB3NzaC1yc2EAAAADAQABAAABAQDGyEBVH7NhCkoQHGMddzyK8O1jPorycgPZbLTu43lwSvUWqjxcevPShwaul7u7jDxNG3GCWlx70giAZOjrENzkP9zrZ0hgmoqxxKN4S0UFYJGDMLdtizR3ePph8Jkl/eMfJq2f9xuo1YKaN6YGqeVY9LwkjOYGJw0PgQJCZXTmm91FQ802zoqdWO4GA6pGFCp1STJdVasGvb8c7Qt/L0DH7ial8L8pH97flVs+InUBDDWu4CyBL1aroG3UFb+viVeifg7kImhpgU8zfIBNjgbdxKB9n7GnU/63J6x4X413JGQ6M4tAeLryhe6lbG7zpJtc7GARf26OTk0g8l9VswjP \n"
  }
}