# Google News Scraper (`datacortex/google-news-scraper`) Actor

Search Google News and export article title, URL, snippet, source, and publish time.

- **URL**: https://apify.com/datacortex/google-news-scraper.md
- **Developed by:** [datacortex](https://apify.com/datacortex) (community)
- **Categories:** SEO tools, Developer tools
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.50 / 1,000 news articles

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## Google News Scraper

Search Google News and download structured **article listings**: **title, URL, snippet, source, and publish time**.

Built for Apify Console, API, MCP agents, and integrations (Make, Zapier, n8n). One dataset row per article — ready for CSV, Excel, or JSON export.

### What you get

| Field | Example |
| --- | --- |
| `title` | Adidas reports quarterly results |
| `url` | https://www.reuters.com/business/adidas |
| `description` | Adidas said sales rose in the latest quarter… |
| `source` | Reuters |
| `published` | 1 day ago |
| `type` | news |
| `position` | 1 |

Default is **one page per query**. Extra stories from the “additional” strip are written after the main list.

#### Sample output (live)

```json
{
  "query": "adidas",
  "type": "news",
  "position": 1,
  "page": 1,
  "title": "AS Roma and adidas unveil the new third kit for the 2026/27 season",
  "url": "/goto?url=…",
  "description": "AS Roma e adidas unveil the new Third kit for the 2026/27 season, inspired by Fides, the virtue associated with loyalty and unity.",
  "source": "AS Roma",
  "published": "1 day ago",
  "rankOverall": 2
}
```

Article `url` is often a Google `/goto` path, not the publisher’s final URL.

### How to run

1. Open the Actor in Apify Console.
2. Enter one search term per line under **Search queries**.
3. Optional: pages, location, language, max results.
4. Click **Start**. Open the **Output** tab when the run finishes.

#### Example input

```json
{
  "queries": ["adidas"],
  "pages": 1,
  "maxResults": 10
}
```

#### API

```bash
curl -X POST "https://api.apify.com/v2/acts/datacortex~google-news-scraper/runs?token=YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"queries":["adidas"],"pages":1}'
```

Replace `YOUR_TOKEN` with an Apify API token.

### Use with MCP / agents

This is a normal Apify Actor. Agents call it through [Apify MCP](https://docs.apify.com/integrations/mcp) — you do not run a separate MCP process.

Pin this Actor as a tool (after it is public):

```json
{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com?tools=datacortex/google-news-scraper"
    }
  }
}
```

The agent should `fetch-actor-details` on `datacortex/google-news-scraper`, then run it with the same JSON as **Example input** above. Running Actors requires an Apify token (OAuth in the client, or `Authorization: Bearer <APIFY_TOKEN>`).

### Pricing

**$0.50 per 1,000 results** + $0.001 per run.

| Event | When it fires | Price |
| --- | --- | --- |
| `apify-actor-start` | Once when the run starts | **$0.001** |
| `apify-default-dataset-item` | Once per dataset row (one article) | **$0.0005** ($0.50 / 1,000) |

| Job | Rows | You pay |
| --- | --- | --- |
| 1 query, 10 articles | 10 | $0.001 + $0.005 = **$0.006** |
| 10 queries | ~100 | $0.001 + $0.050 = **$0.051** |
| 20 queries | ~200 | $0.001 + $0.100 = **$0.101** |
| 70 queries | ~700 | $0.001 + $0.350 = **$0.351** |

Set a **max total charge per run** so a long list cannot overrun budget. The Actor stops when that limit is reached.

### Input reference

| Field | Required | Default | Notes |
| --- | --- | --- | --- |
| `queries` | yes | — | One term per line, max 1,000 |
| `pages` | no | 1 | 1–10; each extra page is another lookup |
| `geoLocation` | no | — | City, state, country, or coordinates |
| `locale` | no | — | Accept-Language value |
| `maxResults` | no | all | Hard cap across every query |

### Limitations

- Article `url` is often a Google `/goto` path, not the publisher’s final URL.
- Publish times are relative strings from the results page (`1 day ago`), not ISO timestamps.
- Failed queries write one `type: "error"` row so you can see which term failed.

### Changelog

See [CHANGELOG.md](CHANGELOG.md).

# Actor input Schema

## `queries` (type: `array`):

One search term per line.

## `pages` (type: `integer`):

Result pages per query (1–10). Page 2 is a second lookup.

## `geoLocation` (type: `string`):

Optional city, state, country, or coordinates for localized results.

## `locale` (type: `string`):

Optional Accept-Language value (Google page language).

## `maxResults` (type: `integer`):

Stop after this many dataset rows across every query. Leave empty to keep every article.

## Actor input object example

```json
{
  "queries": [
    "adidas"
  ],
  "pages": 1
}
```

# Actor output Schema

## `results` (type: `string`):

Dataset of flattened Google News listings.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "queries": [
        "adidas"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("datacortex/google-news-scraper").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "queries": ["adidas"] }

# Run the Actor and wait for it to finish
run = client.actor("datacortex/google-news-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "queries": [
    "adidas"
  ]
}' |
apify call datacortex/google-news-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,datacortex/google-news-scraper"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/CXYA9VbRVK4JemMP6/builds/6339Lv8eRGGHBV4Jr/openapi.json