How to use Google Ads Transparency Scraper

Step by step: in the Apify Store, over the API, from JavaScript or Python, in n8n, and from AI agents through MCP or LangChain.

$1.80 per 1,000 ads on the Free plan, down to $1.35 on higher plans (live Apify price on 2026-11-03).

1. In the Apify Store (no code)

1. Open arcadium/google-ads-transparency and sign in to Apify (a free account works).
2. Fill in the input form. The fields below are the ones the example uses.
3. Set a maximum cost per run in the run options if you want a hard cap.
4. Start the run. Rows appear in the Output tab as they arrive.
5. Export the dataset as JSON, CSV or Excel, or connect an integration.

Example input:

{
  "searchTerms": [
    "nike.com"
  ],
  "mode": "ads",
  "maxAdsPerAdvertiser": 20
}

2. Over the Apify API

The synchronous endpoint runs the actor and returns its rows in one call (for runs up to about five minutes; use the asynchronous run endpoint for longer ones).

curl -X POST "https://api.apify.com/v2/acts/arcadium~google-ads-transparency/run-sync-get-dataset-items" \
  -H "Authorization: Bearer $APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"searchTerms":["nike.com"],"mode":"ads","maxAdsPerAdvertiser":20}'

3. From JavaScript

// npm install apify-client
import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('arcadium/google-ads-transparency').call({
  "searchTerms": [
    "nike.com"
  ],
  "mode": "ads",
  "maxAdsPerAdvertiser": 20
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

4. From Python

# pip install apify-client
import os
from apify_client import ApifyClient

client = ApifyClient(os.environ["APIFY_TOKEN"])
run = client.actor("arcadium/google-ads-transparency").call(run_input={
    "searchTerms": ["nike.com"],
    "mode": "ads",
    "maxAdsPerAdvertiser": 20,
})
items = client.dataset(run.default_dataset_id).list_items().items  # apify-client 3.x returns a Run object
print(items)

5. In n8n

Paste this node into a workflow (it is a plain HTTP Request node). Create a Header Auth credential with name Authorization and value Bearer <APIFY_TOKEN>; each returned row becomes one item for the next node.

{
  "nodes": [
    {
      "name": "Run arcadium/google-ads-transparency",
      "type": "n8n-nodes-base.httpRequest",
      "typeVersion": 4,
      "position": [
        0,
        0
      ],
      "parameters": {
        "method": "POST",
        "url": "https://api.apify.com/v2/acts/arcadium~google-ads-transparency/run-sync-get-dataset-items",
        "authentication": "genericCredentialType",
        "genericAuthType": "httpHeaderAuth",
        "sendBody": true,
        "specifyBody": "json",
        "jsonBody": "{\"searchTerms\":[\"nike.com\"],\"mode\":\"ads\",\"maxAdsPerAdvertiser\":20}",
        "options": {
          "timeout": 300000
        }
      }
    }
  ],
  "connections": {}
}

6. From an AI assistant (MCP)

Add Apify’s MCP server to Claude Desktop, Cursor, VS Code or any MCP client, limited to this actor:

{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com/?tools=arcadium/google-ads-transparency",
      "headers": {
        "Authorization": "Bearer <APIFY_TOKEN>"
      }
    }
  }
}

More on the MCP page.

7. From LangChain

# pip install langchain-apify   (reads APIFY_API_TOKEN from the environment)
from langchain_apify import ApifyActorsTool

tool = ApifyActorsTool("arcadium/google-ads-transparency")
rows = tool.invoke({"run_input": {
    "searchTerms": ["nike.com"],
    "mode": "ads",
    "maxAdsPerAdvertiser": 20,
}})
# or give `tool` to an agent: create_react_agent(llm, [tool])

Sample output

One row, from the example in the actor’s README. Long text is shortened and lists are cut to two items.

{
  "rowType": "ad",
  "platform": "google-ads-transparency",
  "advertiserId": "AR04217635482122584065",
  "advertiserName": "Spotify USA Inc",
  "advertiserNameWithheld": false,
  "advertiserCountry": "US",
  "creativeId": "CR08508353801336389633",
  "adUrl": "https://adstransparency.google.com/advertiser/AR04217635482122584065/creative/CR08508353801336389633?region=GB",
  "format": "video",
  "firstShown": "2025-03-18",
  "lastShown": "2026-10-22",
  "daysShown": 520,
  "regionsShown": [
    "GB",
    "FR"
  ],
  "detailed": true,
  "impressionsMin": 500000,
  "impressionsMax": 600000,
  "regionStats": [
    {
      "region": "FR",
      "firstShown": "2025-03-25",
      "lastShown": "2026-10-21",
      "impressionsMin": 40000,
      "impressionsMax": 45000,
      "platforms": [
        {
          "platform": "youtube",
          "impressionsMin": 35000,
          "impressionsMax": 40000
        }
      ]
    }
  ],
  "contentKind": "video",
  "youtubeVideoId": "2BfJuvCtfEI",
  "youtubeUrl": "https://www.youtube.com/watch?v=2BfJuvCtfEI",
  "searchTerm": "AR04217635482122584065",
  "matchedBy": "advertiser"
}

Tutorials

• Google Ads Transparency scraper: export a competitor’s ads with ad copy and regions

Schedule it

In Apify Console, create a Task from your input and add a Schedule (for example daily). Each run writes a new dataset; integrations can push the rows to Google Sheets, Slack, a webhook or your database.