Google Maps Extractor

What is Google Maps Extractor?

Google Maps Extractor turns a keyword plus location, or a list of Google Maps search and place URLs, into a dataset of places. Each row is one business or place with its name, category, full address, phone, website, Google rating and review count, latitude and longitude, Maps URL, place ID, a permanent-closure flag and the query that found it. Local SEO agencies, B2B sales teams, market researchers and AI agents use it to build local business lists, map competitors and enrich CRMs from a single search.

Why teams use it

• Plain search in, place rows out. searchQuery: "dentists" with location: "Miami, FL" is all it takes.
• Paste existing Maps links. startUrls accepts Google Maps search and place URLs when you already have them.
• Quality filters. minRating keeps only well-rated places, and skipClosedPlaces drops businesses marked permanently closed.
• Local language and country. language sets the Maps interface language for names and categories, and countryCode routes the browser through that country.
• Optional website contacts. includeWebsiteContacts scans each listed website for a public email and Facebook, Instagram, LinkedIn and X links.

Best fit for this Actor

• Designed for place lists by niche and area: dentists in a city, coworking spaces in a district, roofers across a region.
• Best fit for lead lists, local competitor maps, local SEO audits and agent workflows that need structured place records.
• When you need the review text behind each rating, then pass the google_maps_url values to Google Maps Reviews Scraper.
• When email addresses are the main goal, use Google Maps Email Extractor for an email-first workflow.
• To pull deeper contact details from the websites you collect here, continue with Contact Details Scraper.

Example workflow: a local SEO competitor map

A local SEO consultant starts with searchQuery: "dentists", location: "Miami, FL", maxResults at 100 and minRating at 4. The dataset returns every practice's category, address, phone, website, rating and review count with coordinates. She sorts by review_count to see who dominates reviews, compares her client's rating and category with the top ten, plots latitude and longitude on a map to spot underserved neighborhoods, then exports the list as CSV for the client report. A monthly schedule with the same input shows how the competitive set changes.

Input

{
  "searchQuery": "dentists",
  "location": "Miami, FL",
  "maxResults": 20,
  "minRating": 4,
  "skipClosedPlaces": true,
  "includeWebsiteContacts": false,
  "language": "en",
  "countryCode": "US"
}

With Google Maps URLs instead of a keyword:

{
  "startUrls": [{ "url": "https://www.google.com/maps/search/coffee+shops+Austin+TX" }],
  "maxResults": 10
}

Field	Type	What it controls
searchQuery	string	Business type or keyword, such as coffee shops.
location	string	City, region or country, such as London, UK.
startUrls	array	Google Maps search or place URLs as { "url": "..." } objects.
maxResults	integer	Places returned and charged, 1 to 2000. Default 20.
minRating	number	Keep places at or above this rating, 0 to 5. Default 0 keeps all.
skipClosedPlaces	boolean	Skip permanently closed places. Default true.
includeWebsiteContacts	boolean	Scan listed websites for a public email and social links. Default false.
language	string	Google Maps interface language such as en, de or ja. Default en.
countryCode	string	Two-letter proxy country such as US, GB or DE. Default US.

Output

One dataset row per place.

Field	What it contains
business_name, category	Place name and primary Google Maps category
full_address, phone, website	Address, phone and listed website
rating, review_count	Google rating and total review count
latitude, longitude	Coordinates of the place
google_maps_url, place_id	Direct place link and Google feature ID
is_permanently_closed	Permanent-closure flag
website_email, facebook_url, instagram_url, linkedin_url, x_url	Public contact links from the website scan, with includeWebsiteContacts
source_query, scraped_at	The query that found the place and the collection time

{
  "business_name": "Relax and Smile Dental Care",
  "website_email": null,
  "phone": "(786) 983-4812",
  "website": "https://www.relaxandsmile.com/",
  "full_address": "271 NE 2nd St, Miami, FL 33132",
  "category": "Dental clinic",
  "rating": 4.9,
  "review_count": 932,
  "latitude": 25.7763227,
  "longitude": -80.1887702,
  "google_maps_url": "https://www.google.com/maps/place/Relax+and+Smile+Dental+Care/data=!4m7!3m6!1s0x88d9b69ef54365f1:0x9d56ac0453fc14e!8m2!3d25.7763227!4d-80.1887702",
  "place_id": "0x88d9b69ef54365f1:0x9d56ac0453fc14e",
  "facebook_url": null,
  "instagram_url": null,
  "linkedin_url": null,
  "x_url": null,
  "is_permanently_closed": false,
  "scraped_at": "2026-10-01T01:46:20.935Z",
  "source_query": "dentists in Miami, FL"
}

Each run also writes an OUTPUT record to the default key-value store with a machine-readable run summary. Export the dataset as JSON, CSV, Excel, XML or HTML.

Pricing

This Actor uses Pay per event plus Apify platform usage. The events are:

• Actor Start, once per run.
• Place scraped, once for each place row returned to the dataset.

Worked example: dentists in Miami, FL with maxResults set to 50 returns up to 50 places, so the run costs one Actor Start event plus one Place scraped event per place returned, plus the browser and proxy usage of the run. maxResults caps both the dataset and the place charges. Check the live Pricing tab on this page for current event prices.

API example

curl -X POST "https://api.apify.com/v2/acts/khadinakbar~google-maps-extractor/run-sync-get-dataset-items?token=YOUR_API_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"searchQuery": "coffee shops", "location": "Austin, TX", "maxResults": 20}'

from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")
run = client.actor("khadinakbar/google-maps-extractor").call(
    run_input={"searchQuery": "dentists", "location": "Miami, FL", "maxResults": 20, "minRating": 4}
)
for place in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(place["business_name"], place["rating"], place["phone"], place["website"])

Use it with AI agents (MCP)

Connect the Actor to Claude, ChatGPT, Cursor or another MCP client through Apify MCP, then ask:

Find 30 coworking spaces in Berlin rated 4 or higher. Return name, address, phone, website and rating, and group them by district.

The agent reads place rows with get-dataset-items, can cite google_maps_url and scraped_at as provenance, and checks the OUTPUT record for the run summary. Cost scales with places returned, so maxResults keeps agent requests scoped.

Best results

Starting situation	Helpful action	Expected outcome
A large market such as a whole state	Split by city, postal code or neighborhood	Fuller coverage per area
A non-English market	Set language and countryCode to match, such as de and DE	Local names, categories and addresses
Lead lists with quality bar	Set minRating, keep skipClosedPlaces on	Active, well-rated businesses only
You also want social links	Turn on includeWebsiteContacts	Public email and social profile links where websites list them
A first test	Start with maxResults between 5 and 10	A quick, low-cost sample

Builder's note

I built this for the most common Maps job: a clean list of places for a niche and an area, with the same columns every time. I designed one row to equal one place and one charge, so maxResults is both the dataset size and the budget. Website contact scanning is optional because I found most local SEO and market-research runs only need the Maps fields, while lead-generation runs can switch it on.

FAQ

Does it collect reviews?

It returns each place's rating and review count. For review text, use the Google Maps Reviews Scraper linked above.

Can I search in other countries and languages?

Yes. Set location to the area, language to the interface language and countryCode to the matching country.

How do I get emails?

Turn on includeWebsiteContacts for public emails and social links listed on business websites, or use the Google Maps Email Extractor for an email-first workflow.

Responsible use

This Actor extracts publicly visible Google Maps place data and, optionally, public links from listed business websites. Use the output in line with Google's terms, privacy rules and anti-spam laws such as CAN-SPAM and the GDPR. Google Maps is a trademark of Google, and this independent Actor is not affiliated with or endorsed by Google. For questions, open a ticket in the Issues tab.