Apify Google Jobs Scraper

Google Jobs Scraper With Per-Result Billing

A Google Jobs scraper that charges for every listing it hands you and nothing else. Give it a role and a location, get one flat row per opening, and know the bill before the run starts because the math is results times price.

When to use this skill

• The user asks for a "google jobs scraper" or wants to scrape Google Jobs openings.
• They want listings for a role, company, city, or country as a flat dataset.
• They want cost that scales with rows delivered rather than pages fetched.
• They want to exclude specific employers or job boards from the output.

Not for: salary analytics (there is no numeric salary field), LinkedIn-only listings (use the LinkedIn Jobs API), or employer reviews (use the Glassdoor Reviews API).

What you get (one flat row per listing)

Verified on a live run:

• title and job_title (identical strings, so pick either one)
• company_name, location, via (the platform hosting the listing, such as LinkedIn or a company careers site)
• description (full posting text, often 1,500 characters or more)
• job_highlights (array of {title, items} blocks such as Qualifications, Responsibilities, Benefits)
• extensions (raw tag strings such as "22 hours ago", "Full-time")
• detected_extensions (posted_at and schedule_type on every row, plus work_from_home and qualifications when present on that listing)
• apply_options (array of {title, link} direct apply links, one per hosting platform)
• source_link (canonical link to the posting), share_link (Google Jobs permalink), job_id (dedupe key)
• Echoed run context on every row: query, country, language, google_domain, search_timestamp, total_jobs_found, pages_processed

Every row carries its own search context, so you can merge several runs into one table and still tell where each listing came from.

Prerequisites

• Apify account (sign up at https://apify.com?fpr=9n7kx3&fp_sid=skillrepo).
• Authentication via apify login, or an APIFY_TOKEN environment variable (Apify Console, Settings, Integrations).

The Actor

• Store page: https://apify.com/johnvc/google-jobs-scraper---pay-per-result?fpr=9n7kx3&fp_sid=skillrepo
• Actor ID: johnvc/google-jobs-scraper---pay-per-result
• Pricing: pay per result delivered to the dataset (see references/gotchas.md).

Run it with the Apify CLI

Scrape a role in a city, capped at 10 listings:

apify actors call "johnvc/google-jobs-scraper---pay-per-result" -i '{"query":"software engineer","location":"Austin, TX","country":"us","language":"en","num_results":10}' \
  --json \
  --user-agent apify-awesome-skills/apify-google-jobs-scraper \
  2>/dev/null

Scrape a country-wide search on a local Google domain, skipping two job boards:

apify actors call "johnvc/google-jobs-scraper---pay-per-result" -i '{"query":"data analyst","location":"United Kingdom","country":"uk","google_domain":"google.co.uk","language":"en","num_results":50,"via_filter_list":["Indeed","ZipRecruiter"]}' \
  --json \
  --user-agent apify-awesome-skills/apify-google-jobs-scraper \
  2>/dev/null

Every call carries the three flags this repo expects: --json (or --format json), --user-agent apify-awesome-skills/apify-google-jobs-scraper, and 2>/dev/null.

Run it from Claude or another AI agent (MCP)

The Actor is MCP-ready. Add the hosted server URL:

https://mcp.apify.com/?tools=actors,docs,johnvc/google-jobs-scraper---pay-per-result

Then ask, for example: "Scrape Google Jobs for 20 warehouse supervisor openings near Columbus and give me the apply links." MCP setup docs: https://docs.apify.com/platform/integrations/mcp

Workflow

1. Build the query. query is the only required field, and it takes a job title, skill, or company name. Add location (city, state, or country) to narrow it.
2. Set localization. Send country and language explicitly. Google Jobs returns nothing when neither is supplied, and the Actor has to guess from google_domain and log a warning.
3. Cap the volume. num_results is the direct cost lever here because you pay per row. The minimum accepted value is 10; the maximum is 1000.
4. Filter before you pay. company_filter_list and via_filter_list drop matching rows during collection, so excluded listings never reach the dataset and never get billed.
5. Estimate cost, then confirm with the user if the run is large. See references/gotchas.md.
6. Run the Actor and read the dataset. Dedupe across runs on job_id.

Inputs

• query (string, required): job title, skill, or company
• location (string): city, state, or country. Empty plus a country value falls back to the country name
• country (enum: None, us, ca, uk, de, fr, au, jp, in, br, mx)
• language (enum, 100 plus codes, default None)
• google_domain (enum, default google.com)
• num_results (integer 10 to 1000, default 100): the billing lever
• max_pagination (integer 0 to 100, default 0 = unlimited)
• company_filter (string, comma separated) or company_filter_list (array): exclude employers
• company_filter_regex (boolean, default false): treat the company filters as regular expressions
• via_filter (string) or via_filter_list (array): exclude source platforms
• include_lrad (boolean) plus lrad_value (string, miles): radius search
• max_delay (integer 0 to 10, default 1): seconds between requests
• output_file (string): custom filename for the saved results file

Cost

Billing is per result in the default dataset. Ten listings cost ten result charges, one hundred listings cost one hundred. Live per-result prices and confirmation thresholds are in references/gotchas.md.

Honest limits

• No numeric salary field and no experience-level field. Pay figures sometimes appear inside job_highlights Benefits text, but that is free text you would have to parse yourself, not a structured field.
• posted_at is a relative string such as "22 hours ago", so freshness filtering happens on your side after the run.
• pages_processed came back as 0 on the verified run, so treat it as unreliable and count dataset rows instead.
• Google Jobs inventory varies by region and query, so num_results is a cap and not a guarantee.
• Company and source filters are case sensitive unless you turn on company_filter_regex.

Troubleshooting

• No results: send country and language explicitly, then broaden the query or drop the location.
• Fewer rows than num_results: normal, Google had fewer listings for that query.
• Insufficient funds: the Actor writes a single error row explaining the shortfall instead of failing silently. Add funds or lower num_results.

See references/gotchas.md for cost guardrails and error recovery, and references/actor-index.md for the Actor routing table.

Related job-data Actors

• Google Jobs Scraper, pay per page edition: https://apify.com/johnvc/Google-Jobs-Scraper?fpr=9n7kx3&fp_sid=skillrepo
• LinkedIn Jobs API: https://apify.com/johnvc/linkedin-jobs-api?fpr=9n7kx3&fp_sid=skillrepo
• Glassdoor Reviews API: https://apify.com/johnvc/glassdoor-reviews-api?fpr=9n7kx3&fp_sid=skillrepo