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google-jobs-per-result

google-jobs-per-result

Remote
apify.comOther0Updated 6d ago

About google-jobs-per-result

google-jobs-per-result exposes an Apify Google Jobs scraper that returns structured job listings and bills per result. Recruiters and researchers can target searches by location and filter companies or sources before results are returned.

Key features

  1. 01Search Google Jobs by query and location
  2. 02Filter by country, language and radius
  3. 03Exclude companies and job sources
  4. 04Return detailed JSON and apply links
  5. 05Control pagination

Use cases

  1. 01Find localized openings for recruiting
  2. 02Exclude staffing agencies or aggregators
  3. 03Load job records into an ATS or dashboard
  4. 04Analyze job listings by location or source

MCP support

The Apify-hosted MCP endpoint loads this Actor's tools for MCP clients. Clients authenticate through OAuth or an Apify API token to run Google Jobs searches.

Configuration

Remote servers need no local install. Pick your client, then copy the config or install in one click.

Endpointhttps://mcp.apify.com/?tools=johnvc/google-jobs-scraper---pay-per-result
Copy install command
Claude CodeTerminal
Cursor.cursor/mcp.json
VS Code.vscode/mcp.json
Claude Desktopclaude_desktop_config.json
Windsurf~/.codeium/windsurf/mcp_config.json

Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.

Tools

Details

From the project README

💼 Google Jobs API (Pay Per Result): Job Listings in Clean JSON

Pay only for the results you get. The developer-friendly way to use the Google Jobs API.

Actor page: apify.com/johnvc/google-jobs-scraper---pay-per-result Input schema: apify.com/johnvc/google-jobs-scraper---pay-per-result/input-schema

This edition of the Google Jobs API bills per result returned, so your cost scales directly with the number of listings you keep. It searches Google Jobs and returns clean, structured JSON, one record per listing. Each job includes title, company, location, source platform, the full description, parsed metadata (posting date, schedule type, benefits), and direct apply links across platforms (LinkedIn, Indeed, company site, and more). Built-in company and source filters let you drop unwanted results before you pay for them. Supports location targeting, location-radius search, country and language filtering, and pagination.

Prefer per-page pricing instead of per-result? See the pay-per-page edition.

Video Walkthrough

Watch the walkthrough

Quick Start

Prerequisites
  1. Clone the repository

    git clone https://github.com/johnisanerd/Apify-Google-Jobs-Pay-Per-Result.git
    cd Apify-Google-Jobs-Pay-Per-Result
    
  2. Install dependencies with UV

    # Install UV if you do not have it:
    curl -LsSf https://astral.sh/uv/install.sh | sh
    
    # Install project dependencies:
    uv sync
    
  3. Configure your API key

    cp .env.example .env
    # Edit .env and add your Apify API key
    # Get your free API key at: https://apify.com?fpr=9n7kx3
    
  4. Run the example

    uv run python google-jobs-pay-per-result-scraper.py
    
Alternative: set the API key directly
export APIFY_API_TOKEN="your_api_key_here"
uv run python google-jobs-pay-per-result-scraper.py

Why Use This Google Jobs API?

Pay only for results. Billing is per result returned, with no subscription. You decide how many listings to keep, and that is exactly what you pay for.

Filter before you pay. Built-in company and job-source filters (with optional regex matching) let you exclude staffing agencies, aggregators, or specific employers, so you are not charged for results you do not want.

One record per job, fully detailed. Every listing comes with title, company, location, source, the full description, and parsed metadata, so you can load it straight into an ATS, a dashboard, or an analysis pipeline.

Direct apply links. Each job includes apply options across platforms (LinkedIn, Indeed, the company careers site, and more) with direct URLs.

Targeted search. Filter by location, country, language, and Google domain, and use location-radius search to focus on a specific area.

Easy to automate. Call it from Python in a few lines, or load it as an MCP tool so assistants like Claude and Cursor can search jobs for you on demand.

Features

Core Capabilities
  • Job search with location, country, language, and Google-domain targeting
  • Location-radius search to focus results on a specific area
  • Company filters to exclude specific employers (single value, list, or regex)
  • Job-source filters to exclude specific platforms such as aggregators
  • Pagination control with a configurable page cap
  • Direct apply links across multiple platforms per job
Data Quality
  • One record per job with a stable structure
  • Full description text plus parsed metadata (posting date, schedule type, benefits)
  • Apply options with platform names and direct URLs
  • Search metadata echoed on every record
  • Consistent JSON shape across every query

Usage Examples

Basic search
{
  "query": "Software Engineer",
  "location": "Austin, TX",
  "num_results": 10
}
Exclude job sources and a company, with localization
{
  "query": "Data Scientist",
  "location": "Berlin, Germany",
  "country": "de",
  "language": "de",
  "num_results": 20,
  "via_filter_list": ["ZipRecruiter"],
  "company_filter": "Staffing Agency A"
}

Input Parameters

ParameterTypeRequiredDefaultDescription
querystringYes-Job search query, e.g. Software Engineer, Data Scientist.
locationstringNo-Job location (city level recommended), e.g. Austin, TX. Leave empty for a worldwide search.
countrystringNoNoneCountry code (ISO 3166-1 alpha-2), e.g. us, de.
languagestringNoNoneLanguage code for results, e.g. en.
google_domainstringNogoogle.comGoogle domain to search.
num_resultsintegerNo100Maximum number of job results to return. Minimum accepted is 10. Each returned result is billed.
max_paginationintegerNo0Maximum pages to fetch (~10 results each); 0 = unlimited.
include_lradbooleanNofalseEnable location-radius filtering.
lrad_valuestringNo5Radius in miles when include_lrad is true.
max_delayintegerNo1Delay in seconds between requests, to avoid rate limiting.
company_filterstringNo-Exclude jobs from specific companies; single name or comma-separated list.
company_filter_listarrayNo-Exclude companies as a list; takes precedence over company_filter.
company_filter_regexbooleanNofalseTreat company filters as regex patterns for flexible matching.
via_filterstringNo-Exclude jobs from specific sources/platforms; single name or comma-separated list.
via_filter_listarrayNo-Exclude sources as a list; takes precedence over via_filter.
output_filestringNo-Optional filename to save results.

Output Format

A real result for Software Engineer in Austin, TX (one item per job; the full description, extensions, and detected_extensions are present but omitted here for readability, and job_id is truncated).

{
  "title": "Senior Software Engineer",
  "company_name": "Southwest Airlines",
  "location": "Austin, TX",
  "via": "Southwest Careers - Southwest Airlines",
  "apply_options": [
    {
      "title": "Southwest Careers - Southwest Airlines",
      "link": "https://careers.southwestair.com/us/en/job/R-2026-68331/Senior-Software-Engineer"
    }
  ],
  "job_id": "eyJqb2JfdGl0bGUiOiJTZW5pb3IgU29mdHdhcmUgRW5naW5lZXIiLCJjb21wYW55X25hbWUiOi...",
  "query": "Software Engineer",
  "country": "us",
  "language": "en",
  "google_domain": "google.com",
  "search_timestamp": "2026-05-29T11:21:31",
  "total_jobs_found": 10,
  "pages_processed": 1
}

Each job record also includes the full description text, an extensions array of raw tags (for example Full-time), a detected_extensions object with parsed fields like posting date and schedule type, plus share_link, source_link, and job_title.


Use as an MCP tool

You can load the Google Jobs API as an MCP tool so assistants call it for you. The MCP server URL preloads just this one Actor:

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

Authenticate with OAuth in the browser when offered, or with your Apify API token (the same APIFY_API_TOKEN used by the Python example). Get a token at https://console.apify.com/settings/integrations and a free Apify account at https://apify.com?fpr=9n7kx3 .

Install in Claude Cowork Desktop

Install in Claude Cowork Desktop

Cowork is the desktop app's automation mode. To give it the Google Jobs API as a tool, add the Apify MCP server as a connector.

  1. Open the Claude desktop app and go to Settings → Connectors (or Settings → Developer → Edit Config to edit claude_desktop_config.json directly).
    • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
    • Windows: %APPDATA%\Claude\claude_desktop_config.json
  2. Add the Apify MCP server, preloaded with only this Actor:
{
  "mcpServers": {
    "apify": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-remote",
        "https://mcp.apify.com/?tools=actors,docs,johnvc/google-jobs-scraper---pay-per-result"
      ]
    }
  }
}
  1. Restart the app. When Cowork first calls the tool, complete the OAuth prompt in your browser, or add your Apify API token in the connector settings to skip OAuth.
  2. In a Cowork chat, confirm the tool is available and ask it to run the Google Jobs API.

Download the desktop app and start a free trial: https://claude.ai/referral/uIlpa7nPLg More help: https://docs.apify.com/platform/integrations/claude-desktop

Install in Claude Code

Install in Claude Code

Claude Code is the command-line tool. Add the Actor's MCP server with one command:

claude mcp add --transport http apify \
  "https://mcp.apify.com/?tools=actors,docs,johnvc/google-jobs-scraper---pay-per-result"

To use a token instead of browser OAuth:

claude mcp add --transport http apify \
  "https://mcp.apify.com/?tools=actors,docs,johnvc/google-jobs-scraper---pay-per-result" \
  --header "Authorization: Bearer YOUR_APIFY_TOKEN"

Then verify with claude mcp list, or run /mcp inside a session. Ask Claude Code to call the Google Jobs API.

Try Claude Code free: https://claude.ai/referral/uIlpa7nPLg Claude Code MCP docs: https://code.claude.com/docs/en/mcp

Install in Claude (website)

Install in Claude (website)

On claude.ai you add Apify as a connector, then enable just this Actor's tool.

  1. Go to Settings → Connectors → Browse connectors and search for Apify MCP server. Install it (enable or update if prompted).
  2. When connecting, authenticate with your Apify API token, and enable the tool johnvc/google-jobs-scraper---pay-per-result.
  3. In any chat, open + → Connectors and turn on Apify.
  4. Alternatively, choose Add custom connector and paste the full MCP URL https://mcp.apify.com/?tools=actors,docs,johnvc/google-jobs-scraper---pay-per-result, using OAuth when prompted.
  5. Ask Claude to run the Google Jobs API.

Open Claude on the web: https://claude.ai/referral/uIlpa7nPLg

Install in Cursor

Install in Cursor

Cursor reads MCP servers from a project file at .cursor/mcp.json.

  1. In your project, create .cursor/mcp.json:
{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com/?tools=actors,docs,johnvc/google-jobs-scraper---pay-per-result"
    }
  }
}
  1. If you prefer token auth over browser OAuth, add a header:
{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com/?tools=actors,docs,johnvc/google-jobs-scraper---pay-per-result",
      "headers": { "Authorization": "Bearer YOUR_APIFY_TOKEN" }
    }
  }
}
  1. Open Cursor → Settings → MCP and confirm the apify server is connected (green dot).
  2. In Composer or Chat, ask Cursor to call the Google Jobs API.

New to Cursor? Get it here: https://cursor.com/referral?code=XQP4VBLI3NNX

Install in ChatGPT

Install in ChatGPT

ChatGPT connects to the Apify MCP server through Developer mode (available on ChatGPT Pro, Plus, Business, Enterprise, and Education plans).

  1. Click your profile icon, then go to Settings > Apps. If you do not see a Create app button, open Advanced settings and enable Developer mode.
  2. Click Create app and fill out the form:
    • Name: Apify
    • MCP Server URL: https://mcp.apify.com/?tools=actors,docs,johnvc/google-jobs-scraper---pay-per-result
    • Authentication: OAuth
  3. Click Create and authorize the connection with Apify.
  4. To use the app in a conversation, click + in the chat, choose Developer mode, and select Apify.

More help: https://docs.apify.com/platform/integrations/mcp


Made with care

Use the Google Jobs API to power recruiting tools, market research, and analytics with reliable, structured results.

Featured Tasks

Ready-to-run examples on the Apify Store.

🤖 Ask an AI assistant about this Actor

Open a ready-to-send prompt about the Google Jobs Scraper API in the AI of your choice:

Last Updated: 2026.10.27

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