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google_jobs

Scrape Google Jobs listings by query and country to get titles, companies, salaries, posted dates and apply links without a browser. Use it to gather job market data at low cost.

Instructions

Google Jobs Scraper (Cheap, No Browser)

Scrape Google Jobs listings by query and country: title, company, location, source (LinkedIn, Indeed...), posted date, salary, job type, description and apply links. No browser. $1.00 per 1,000 jobs plus Google SERP proxy usage.

Pricing (pay per event, billed to your Apify account): Job: $0.001; platform usage billed to your account.

Runs on Apify as subimpact/google-jobs-scraper.

Input Schema

NameRequiredDescriptionDefault
queriesNoOne or more Google Jobs searches, e.g. `software engineer jobs kuala lumpur` or `barista jobs singapore`. Each query returns Google's first Jobs page (about 10 listings). Add more queries to cover more jobs. Maximum 100 queries per run.
locationNoFree text appended to every query, e.g. `Kuala Lumpur` or `remote`. Leave empty to search the query exactly as written. The country code still controls the Google country setting.
maxItemsNoGlobal cost ceiling: the run stops after this many job rows, across all queries. At $0.001 per job, 100 rows cost $0.10 plus proxy usage. The default single query returns about 10 jobs, so a default run costs about $0.01 plus proxy usage. Hard cap 1,000.
_maxItemsNoHow many dataset items to return to the model (1-1000, default 50). Truncates the response only; it does not change what the Actor collects or charges for.
concurrencyNoHow many queries are fetched in parallel. Higher is faster but uses more proxy sessions at once. Default 5.
countryCodeNoTwo-letter country code used for the Google country setting. Examples: us, my, sg, gb, au, ca, in. `uk` is accepted and mapped to gb.us
languageCodeNoGoogle interface language. Use a two-letter code like en, ms, de, or a regional code like en-MY.en
_maxChargeUsdNoPer-run spending cap in USD (default 0.5). Passed to Apify as the run option maxTotalChargeUsd, so the run stops when it reaches this charge.
maxJobsPerQueryNoGoogle shows about 10 jobs per search and has no working page 2 (verified October 2026). To collect more, add more specific queries (role + city, or different locations).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.5/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full behavioral burden and usefully discloses that the tool runs without a browser, runs on Apify, bills per job and for proxy usage, and lists the fields returned. It does not cover authentication details, rate limits, or reliability characteristics, but the cost and execution model disclosure is strong.

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 generally front-loaded and appropriately sized, starting with the purpose and output fields. The pricing is stated twice in slightly different forms, which is redundant, but the overall structure remains efficient.

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

Completeness4/5

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

There is no output schema, so the description appropriately lists the fields returned, and it also explains the no-browser execution and billing model. Given the fully documented input schema, the main remaining gap is the absence of guidance on alternatives or operational constraints like rate limits.

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?

Schema description coverage is 100%, so the input schema already provides detailed parameter semantics. The description only implies query and country inputs and adds no parameter-level meaning beyond what the schema documents.

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 states a specific verb and resource: scrape Google Jobs listings by query and country, and it lists the returned fields. It is clear what the tool does, but it does not explicitly distinguish itself from sibling tools such as company_career_jobs or google_search.

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

Usage Guidelines2/5

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

The description explains what the tool does but gives no explicit guidance on when to use it instead of alternatives like company_career_jobs or google_search. Usage is only implied by the purpose statement.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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