Google Jobs MCP server

💼 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

1. 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

1. 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

1. 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
}

Shortened. The full README is on GitHub.