# Google News Scraper & Media Coverage Intelligence (`azzarilabs/google-news-media-intelligence`) Actor

Turn public Google News coverage into article evidence, publisher context, and coverage summaries.

- **URL**: https://apify.com/azzarilabs/google-news-media-intelligence.md
- **Developed by:** [Azzari Labs](https://apify.com/azzarilabs) (community)
- **Categories:** News, Marketing
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$0.50 / 1,000 article results

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?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## Google News Scraper & Media Coverage Intelligence

Track public Google News coverage for a topic, brand, or competitor. Start with one query and a seven-day window; use the article evidence to decide what merits a media or editorial response.

### Problem → result → decision

Repeated manual news searches make source and recency comparisons slow. Give the Actor a topic and a result cap. It returns unique observed article rows, query summaries, `OUTPUT`, and `REPORT.html`. Use those observations to prioritize follow-up with journalists, publishers, or internal teams. It is not a complete media census.

### Three use cases

1. Monitor visible public coverage of a brand or product.
2. Compare publisher diversity around a competitor topic.
3. Prepare a PR briefing from recent coverage and publication dates.

### Quick Start (<30 seconds)

1. Replace the sample query with a topic, brand, or company.
2. Keep the seven-day window and 25-article cap for the first run.
3. Click Start; inspect the Articles Dataset view, OUTPUT, REPORT, and warnings.

```json
{"queries":["artificial intelligence"],"timeRange":"7d","maxResultsPerQuery":25}
```

Full sample input: `examples/INPUT.json`. Advanced options include public News sections (an alternative to topics), fixed validated US/en-US locale settings, optional publisher URL resolution, and article order. Clear the sample query for a sections-only run.

### Illustrative output row

```json
{"record_type":"article","query":"artificial intelligence","search_position":1,"title":"Illustrative observed headline","source_name":"Example publisher","google_news_url":"https://news.google.com/articles/example","article_url":null,"url_resolved":false,"published_at":null}
```

This is a sanitized schema-shaped illustration, not an observed live article. Publisher URLs and dates can be unavailable. Query-summary rows, OUTPUT, and REPORT explain overlap, source diversity, freshness, and warnings.

### Pricing

`article-result`: USD 0.0005 per unique valid article delivered. At that event rate, 100 / 1,000 / 10,000 articles cost USD 0.05 / 0.50 / 5.00 in event charges. Query summaries, duplicates, empty results, unresolved URL attempts, OUTPUT, and REPORT are not charged. This candidate does not change Cloud pricing.

### Evidence and limits

The Cloud-validated 0.1.3 release delivered four article rows with Dataset, OUTPUT, and REPORT passing in its smoke. That is one observed run, not a reliability claim. US/en-US is the only validated locale. Google News may omit fields or change ranking, and publisher URL resolution is optional and not guaranteed.

**Next step:** Run one topic, review the article evidence, and increase the cap only if it supports a media decision. There is no same-suite cross-link to add in this five-Actor launch set.

# Actor input Schema

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

Enter a topic or brand to monitor. Standard Google News operators are passed through.

## `timeRange` (type: `string`):

Choose how far back to look when Google News supports the time filter.

## `maxResultsPerQuery` (type: `integer`):

Set a modest cap for a quick first run; only valid delivered articles are billed.

## `sections` (type: `array`):

Optional public topic feeds. Clear the sample query if you want a sections-only run.

## `country` (type: `string`):

Only US is validated in this release.

## `language` (type: `string`):

Only en-US is validated in this release.

## `resolvePublisherUrls` (type: `boolean`):

Optional bounded redirect resolution; a publisher URL is not guaranteed.

## `sortBy` (type: `string`):

Keep Google relevance or sort observed dates newest first.

## Actor input object example

```json
{
  "queries": [
    "artificial intelligence"
  ],
  "timeRange": "7d",
  "maxResultsPerQuery": 25,
  "sections": [],
  "country": "US",
  "language": "en-US",
  "resolvePublisherUrls": false,
  "sortBy": "google_relevance"
}
```

# Actor output Schema

## `dataset` (type: `string`):

No description

## `output` (type: `string`):

No description

## `report` (type: `string`):

No description

# 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": [
        "artificial intelligence"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("azzarilabs/google-news-media-intelligence").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": ["artificial intelligence"] }

# Run the Actor and wait for it to finish
run = client.actor("azzarilabs/google-news-media-intelligence").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": [
    "artificial intelligence"
  ]
}' |
apify call azzarilabs/google-news-media-intelligence --silent --output-dataset

```

## MCP server setup

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

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/MSHX2zfcvlv9sC3ju/builds/EXPnqpY80CQ5zO225/openapi.json