Google Trends Scraper: Interest, Regions, Related & Trending

Get Google Trends data for a list of keywords in one run, as clean JSON, CSV or Excel:

• Interest over time: the full 0–100 timeline for each keyword (hourly, daily, weekly or monthly points, depending on the timeframe).
• Interest by region: countries, states/sub-regions, cities or US metro areas (DMA).
• Related queries: top and rising searches, including "Breakout" terms.
• Related topics: top and rising topics (entities such as companies, people and products).
• Trending searches ("Trending now"): today's trending searches per country, with approximate traffic and the news stories behind them.

Any country or region, any timeframe (preset or custom date range), any category, and web, YouTube, News, Image or Shopping search.

Use with AI agents (MCP, Claude, ChatGPT, Cursor)

Purpose: Get Google Trends data for keywords: interest over time (0–100), interest by region, related queries and topics, and today's trending searches, for any country and timeframe.

When to use it

• "Is X growing?", "when does X peak each year?", "which country searches X most?", "compare A vs B".
• Finding rising and Breakout related searches for content or product ideas.
• Daily trending searches per country (trendingSearches: true, works without keywords).

When not to use it

• Values are relative (0–100), not absolute search volumes.
• For long-tail keyword lists, use Keyword Autocomplete.

Example input

{
  "keywords": [
    "electric bike",
    "e-scooter"
  ],
  "geo": "GB",
  "timeframe": "today 5-y",
  "compareKeywords": true,
  "relatedQueries": true,
  "interestByRegion": false,
  "relatedTopics": false
}

Output fields (one dataset item per row): One row per keyword and data type. Common fields: dataType (interestOverTime / interestByRegion / relatedQueries / relatedTopics / trendingSearch), keyword, geo, timeframe, average, comparedWith, timeline (array of {date, formattedTime, value, isPartial}), regions (array of {geoCode, geoName, value}), top / rising (related lists), approxTraffic, trendsUrl, scrapedAt.

Cost: $0.01 per run + $0.004 per result row (one keyword × one data type) + $0.001 per trending search. Turn off data types you do not need to cut cost.

Connect it to your agent: add this remote MCP server (Apify's official MCP server, loaded with just this tool):

{"mcpServers": {"google-trends-scraper-all-in-one": {"url": "https://mcp.apify.com?tools=ryumoon-data/google-trends-scraper-all-in-one"}}}

Or call it from any agent with the Apify API: POST https://api.apify.com/v2/acts/ryumoon-data~google-trends-scraper-all-in-one/run-sync-get-dataset-items with the input above as the JSON body. Agents without an Apify account can pay per run with agentic payments (x402, MPP or Skyfire).

Why this scraper

• All five Trends widgets in one run. You don't need a separate actor for each.
• Built for Google's rate limits. Google Trends answers HTTP 429 ("Too many requests") very quickly. This actor keeps the Trends cookie, waits between requests, retries with exponential back-off and moves to a new residential IP whenever it gets blocked. If a request still fails after all retries, it is skipped and reported in the run's SUMMARY. You're never charged for a skipped request.
• One row per keyword and data type. You get a whole timeline in one row, not hundreds of rows, so it's cheap and easy to use. Flat "timeline" and "regions" dataset views are included for spreadsheets.

Use cases

• Keyword and content research: find rising queries and Breakout topics before competitors do.
• Seasonality: plan stock, campaigns and posts from 5-year weekly timelines.
• Market sizing: compare brands or products (up to 5 at a time) across countries and regions.
• Newsjacking and social: pull today's trending searches every morning on a schedule.
• Feed dashboards, Google Sheets, Make/Zapier/n8n or an AI agent through the Apify API and MCP.

Input

Field	What it does
keywords	Up to 100 search terms.
geo	GB, US, US-CA … or empty for worldwide.
timeframe	now 1-H, now 4-H, now 1-d, now 7-d, today 1-m, today 3-m, today 12-m, today 5-y, all, or 2024-01-01 2024-12-31.
category	Google Trends category ID (0 = all).
searchProperty	web, youtube, news, images, shopping.
interestOverTime, interestByRegion, relatedQueries, relatedTopics	Turn each data type on or off.
compareKeywords	Compare keywords in groups of up to 5, so their values are relative to each other (like the Trends website).
regionResolution	Auto, countries, sub-regions, cities or DMA.
trendingSearches, trendingGeos	Also collect "Trending now" for one or more countries.
proxyConfiguration	Apify Proxy RESIDENTIAL (default, recommended) or your own proxy URLs.
maxRetries, minDelayBetweenRequestsSecs	Reliability tuning.

Example:

{
  "keywords": ["air fryer", "slow cooker"],
  "geo": "GB",
  "timeframe": "today 5-y",
  "compareKeywords": true,
  "trendingSearches": true,
  "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"] }
}

Output

Interest over time (one row per keyword):

{
  "dataType": "interestOverTime",
  "keyword": "air fryer",
  "comparedWith": ["slow cooker"],
  "average": 61,
  "timeline": [
    { "date": "2021-11-07T00:00:00.000Z", "formattedTime": "Nov 7 – 13, 2021", "value": 74, "hasData": true, "isPartial": false }
  ],
  "geo": "GB", "timeframe": "today 5-y", "category": 0, "searchProperty": "web",
  "trendsUrl": "https://trends.google.com/trends/explore?q=air+fryer&geo=GB&date=today+5-y",
  "scrapedAt": "2026-11-02T09:00:00.000Z"
}

Interest by region: regions: [{ "geoCode": "GB-SCT", "geoName": "Scotland", "value": 100 }, …]. Related queries and topics: top: [...] and rising: [...]. Each entry has query (or title, topicId, topicType), value, formattedValue (e.g. +250% or Breakout), isBreakout and a link. Trending search: rank, title, approxTraffic ("2K+"), approxTrafficMin (2000), startedAt, picture and news: [{ title, url, source }].

Pricing (pay per event)

Event	Price
Run start	$0.01 per run
Trends result: one keyword × one data type (a full timeline, region list or related list)	$0.004
Trending search (one row)	$0.001

Examples:

• 1 keyword with all 4 data types = $0.01 + 4 × $0.004 = $0.026.
• 10 keywords with all 4 data types = $0.01 + 40 × $0.004 = $0.17.
• Trending now for 3 countries (about 20 each) = $0.01 + 60 × $0.001 = $0.07.

Residential proxy traffic is included in these prices; you don't pay for it separately. Requests that fail after all retries are not charged, and neither are empty answers. When Google has no data (for example, no related topics for a niche keyword), the row is saved with "noData": true and costs nothing. You can cap the cost of any run with Apify's "Maximum cost per run" setting. The actor stops cleanly when it reaches the cap.

Limits and honest notes

• This actor reads the same public endpoints the Google Trends website uses. Google doesn't publish an official free Trends API, and it can change these endpoints at any time. We fix breakages as quickly as we can.
• Google Trends values are relative (0–100), not absolute search volumes.
• Related topics are often empty for niche keywords or short timeframes, and Google doesn't offer them at all in compare mode (compareKeywords). That comes from Google, not from the scraper. Empty rows are free.
• "Trending now" comes from Google's public trending RSS feed, which usually lists 10–25 searches per country.
• Without a proxy, Google usually blocks cloud servers after the first request or two. Keep the RESIDENTIAL proxy on.
• Very large keyword lists are slower, because the actor paces requests to avoid blocks. Split huge lists into several runs.

FAQ

Is scraping Google Trends legal? The actor collects only public, aggregated and anonymous trend data. No personal data is involved. Make sure your use complies with Google's terms and the laws that apply to you.

Why do numbers differ slightly from the website? Google samples Trends data, so repeated requests can differ by a few points. That happens on the website too.

Can I run it on a schedule? Yes. Use Apify Schedules, for example every morning for trending searches or weekly for keyword timelines.