Indeed Jobs, Salary & Company Data Scraper

Scrape public Indeed job search results and return titles, companies, locations, salary text, snippets, posting age and source URLs as structured rows for recruiting, salary research and workforce analytics.

Business use and first result

For: Recruitment and compensation research.

Why run it: Collect public Indeed job posts to analyze advertised jobs, employers, locations and salary descriptions.

What to inspect: Job title, company, location, available salary text, posting context and source URL.

First run: use the documented sample input below, inspect the Dataset rows and source links, then reuse the saved output for a later comparison only where snapshots are supported. Confirm the input scope and current Pay Per Event pricing before scheduling ongoing use.

Scope and limitations: Salary is often missing or expressed as text, not a verified wage; public source access may change.

Why use this Actor

Teams need current structured source data without repeatedly rebuilding brittle collection workflows.

Key features

• Buyer-native inputs aligned to Indeed jobs salary scraper.
• Predictable structured output in the default Apify Dataset.
• Pay Per Event pricing tied to measurable result rows or reports.
• Optional MCP connector delivery for downstream automation and AI agents.

Quick start

Start with this working example and replace the target values with your own:

{
  "searchQueries": [
    "python developer"
  ],
  "locations": [
    "Remote"
  ],
  "maxItems": 20
}

The Actor writes structured results to the default Apify Dataset and can be used from the Store, API, schedules, Tasks, automations and MCP-compatible AI workflows.

Input

• searchQueries — Job search queries: Indeed search phrases, for example Python developer or registered nurse.
• locations — Locations: Location filters matched with search queries; use Remote for broad remote listings.
• maxItems — Maximum jobs: Maximum structured Indeed job rows returned.
• diagnostic — Diagnostic mode: Return bounded browser diagnostics only if no jobs can be normalized.

All integration and advanced analysis fields are optional. The default example is intentionally runnable without configuring MCP or a previous-run baseline.

Output

The Dataset exposes predictable machine-readable output. Representative fields include results.

Pricing

This Actor uses Pay Per Event. The current factory base price is $0.000900 per result event. The Apify Store remains the source of truth for the price and plan/tier details shown to the buyer.

Use cases

• Run the buyer-ready workflows exposed as Apify Tasks without preparing a custom integration first.
• Use the Actor from API or schedules for recurring collection, comparison or monitoring.
• Feed the structured Dataset output into spreadsheets, databases, automations or AI agents.
• Compare repeat runs when the product supports snapshots or previous-run inputs.

Automation and AI

Use the same Actor through Apify API, schedules, public Tasks and the Apify MCP server. Outputs are structured for downstream workflows and AI agents rather than requiring manual copy/paste.

Limitations

• Public websites and upstream APIs can change markup, access rules, rate limits or field availability without notice.
• Fields that are not publicly available are returned as unavailable or omitted rather than fabricated.
• Analytical outputs depend on the quality and coverage of the supplied or collected source data.
• Treat marketplace, reputation, workforce, safety or commercial signals as decision support and validate material decisions against the underlying source evidence.