💼 Google Jobs API: Job Listings in Clean JSON

The most efficient, reliable, and developer-friendly way to use the Google Jobs API.

Actor page: apify.com/johnvc/Google-Jobs-Scraper Input schema: apify.com/johnvc/Google-Jobs-Scraper/input-schema

The Google Jobs API searches Google Jobs and returns clean, structured JSON, one record per listing. Each job includes title, company, location, source platform, the full description, structured highlights (qualifications, responsibilities, benefits), parsed metadata (posting date, schedule type, benefits), and direct apply links across platforms (LinkedIn, Indeed, company site, and more). Supports location targeting, location-radius search, country and language filtering, and pagination.

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

Video Walkthrough

Quick Start

Prerequisites

• Python 3.11 or higher
• An Apify account and API key (get a free key here)

1. Clone the repository

   git clone https://github.com/johnisanerd/Apify-Google-Jobs-Scraper.git
   cd Apify-Google-Jobs-Scraper
   

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-search-scraper.py
   

Alternative: set the API key directly

export APIFY_API_TOKEN="your_api_key_here"
uv run python google-jobs-search-scraper.py

Why Use This Google Jobs API?

One record per job, fully detailed. Every listing comes with title, company, location, source, the full description, structured highlights, 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.

Predictable, pay-per-use pricing. Billing is per page processed, with no subscription. You control cost with the page limit.

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
• Pagination control with a configurable page cap
• Direct apply links across multiple platforms per job
• Structured highlights: qualifications, responsibilities, benefits

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": "San Francisco, CA",
  "max_pagination": 1
}

Localized search with radius

{
  "query": "Data Scientist",
  "location": "Berlin, Germany",
  "country": "de",
  "language": "de",
  "include_lrad": true,
  "lrad_value": "10",
  "max_pagination": 1
}

Input Parameters

Parameter	Type	Required	Default	Description
query	string	Yes	-	Job search query, e.g. Software Engineer, Data Scientist.
location	string	No	-	Job location (city level recommended), e.g. San Francisco, CA.
country	string	No	(none)	Country code (ISO 3166-1 alpha-2), e.g. us, de.
language	string	No	(none)	Language code for results, e.g. en.
google_domain	string	No	google.com	Google domain to search.
num_results	integer	No	100	Maximum number of job results to return.
max_pagination	integer	No	0	Maximum pages to fetch (~10 results each); 0 = unlimited. Each page is billed separately.
include_lrad	boolean	No	false	Enable location-radius filtering.
lrad_value	string	No	5	Radius in km when include_lrad is true.
output_file	string	No	-	Optional filename to save results.

Output Format

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

{
  "title": "Software Engineer",
  "company_name": "Lockheed Martin",
  "location": "San Francisco, CA",
  "via": "Lockheed Martin Careers",
  "apply_options": [
    {
      "title": "Lockheed Martin Careers",
      "link": "https://www.lockheedmartinjobs.com/job/owego/software-engineer/694/93796107616"
    }
  ],
  "job_id": "eyJqb2JfdGl0bGUiOiJTb2Z0d2FyZSBFbmdpbmVlciIsImNvbXBhbnlfbmFtZSI6...",
  "query": "Software Engineer",
  "country": "us",
  "language": "en",
  "google_domain": "google.com",
  "search_timestamp": "2026-05-29T11:10:36",
  "total_jobs_found": 10,
  "pages_processed": 1
}

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

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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

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

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"
      ]
    }
  }
}

3. 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.
4. 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

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"

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" \
  --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)

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.
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, 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

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"
    }
  }
}

2. 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",
      "headers": { "Authorization": "Bearer YOUR_APIFY_TOKEN" }
    }
  }
}

3. Open Cursor → Settings → MCP and confirm the apify server is connected (green dot).
4. 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

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
   • 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

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Made with care

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

Last Updated: 2026.07.31