Apify Scrape Google Jobs

Scrape Google Jobs: Listings to Structured JSON

Scrape Google Jobs into clean JSON with the Apify Google Jobs Scraper. Give it a job title and an optional location, and get one flat row per listing: title, company, source platform, full description, highlights, posting age, and direct apply links.

When to use this skill

• The user wants to scrape Google Jobs results (to JSON, CSV, a sheet, or a database).
• They want openings for a role, company, city, or country as a dataset.
• They want job listings for research, recruiting pipelines, or market scans.
• They ask for a "Google Jobs scraper", "job scraper", or "job scraping".

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

What you get (one row per listing)

title, company_name, location, via (source platform), description, job_highlights (Qualifications, Responsibilities, Benefits), extensions (raw tags such as "Full-time", "3 days ago"), detected_extensions (posted_at, schedule_type, plus benefit flags such as health_insurance only when a listing advertises them), apply_options (per-platform title plus direct link), job_id, share_link. Run metadata includes total_jobs_found and pages_processed.

Prerequisites

• Apify account (sign up at https://apify.com?fpr=9n7kx3&fp_sid=awesomeskills).
• 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?fpr=9n7kx3&fp_sid=awesomeskills
• Actor ID: johnvc/Google-Jobs-Scraper
• Pricing: pay per page of results processed (see references/gotchas.md).

Run it with the Apify CLI

Scrape a role in a city:

apify actors call "johnvc/Google-Jobs-Scraper" -i '{"query":"software engineer","location":"Austin, TX","num_results":50}' \
  --json \
  --user-agent apify-awesome-skills/apify-scrape-google-jobs \
  2>/dev/null

Scrape a country-wide search on a local Google domain:

apify actors call "johnvc/Google-Jobs-Scraper" -i '{"query":"data analyst","location":"United Kingdom","google_domain":"google.co.uk","num_results":100}' \
  --json \
  --user-agent apify-awesome-skills/apify-scrape-google-jobs \
  2>/dev/null

Every call carries the three flags this repo expects: --json, --user-agent apify-awesome-skills/apify-scrape-google-jobs, 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

Then ask, for example: "Scrape Google Jobs for remote customer service roles and export the listings as JSON." MCP setup docs: https://docs.apify.com/platform/integrations/mcp

Workflow

1. Build the query. query is the only required field: a job title, skill, or company. Add location (city, state, or country) to narrow it.
2. Bound the volume. Set num_results (default 100, about 10 listings per page) and, to hard-cap pages, max_pagination. Start small: 30 to 50 results is one to five pages.
3. Localize when needed. Pick google_domain and language for non-US markets; add include_lrad plus lrad_value for a radius search around the location.
4. Estimate cost, then confirm with the user if the run is large. See references/gotchas.md.
5. Run the Actor and read the dataset. Deliver rows as JSON or CSV, or hand back the dataset link. Dedupe across runs on job_id.

Inputs

• query (string, required): job title, skill, or company
• location (string): city, state, or country
• country (enum, 11 values) and language (enum, 100 plus values)
• google_domain (enum, default google.com)
• num_results (integer, default 100): cap on listings returned
• max_pagination (integer, default 0 = fetch all available up to num_results)
• include_lrad (boolean) plus lrad_value (string, km): radius search
• max_delay (integer, default 1): seconds between page requests

Cost

Billing is per page of results processed, roughly 10 listings per page. A 50-result run is about five pages. Estimate first and confirm large runs; live prices and thresholds are in references/gotchas.md.

Honest limits

• No numeric salary field and no experience-level field; do not promise salary or seniority filters.
• posted_at is a relative string such as "3 days ago", so freshness filtering happens on your side after the run.
• Google Jobs inventory varies by region and query; num_results is a cap, not a guarantee.

Troubleshooting

• No results: broaden the query, or drop the location. For some non-US cities the Actor already retries with the location merged into the query.
• Fewer results than num_results: normal; Google had fewer listings for that query.
• Budget warning at startup: raise the run's budget limit, or lower num_results / set max_pagination.

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 API, pay per result edition: https://apify.com/johnvc/google-jobs-scraper---pay-per-result?fpr=9n7kx3&fp_sid=awesomeskills
• LinkedIn Jobs API: https://apify.com/johnvc/linkedin-jobs-api?fpr=9n7kx3&fp_sid=awesomeskills
• Glassdoor Reviews API: https://apify.com/johnvc/glassdoor-reviews-api?fpr=9n7kx3&fp_sid=awesomeskills