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MCPToolsGoogle Maps Listings

Google Maps Listings

Give it a search query, get back the local businesses Google Maps returns for it.

Tool
google_maps_listings
Cost
0.3 credits
Category
Local Business
Required input
query
Returns
Business listings, optionally with reviews

What it does

  • Returns business listings from Google Maps for a search query, for sourcing local business leads.
  • query is the search itself — for example "dentists in Austin".
  • location narrows the search to a city or area, for example "Austin, TX".
  • include_reviews scrapes each place detail page for reviews and richer data. It costs the same, but it does more work per place.
  • max_results sets how many listings come back — 1 to 100, default 10.

This is the standard first step of a local-business list build. Listings give you names and websites; they do not give you contacts. Chain scrape_emails_from_website on each website to get an address you can write to.


Parameters

ParameterTypeRequiredNotes
querystringYese.g. "dentists in Austin"
locationstringNoCity or area, e.g. "Austin, TX"
include_reviewsbooleanNoScrapes each place detail page for reviews and richer data
max_resultsnumberNo1–100, default 10

How to use it

Connect the MCP server

Follow the setup guide for your client. Browser sign-in, no API key.

Pull the listings

Get Google Maps listings for "dentists in Austin", location Austin, TX, 50 results.

Add reviews when you need to qualify

Same search, but include reviews. Rank the practices by review count and flag anything rated under 4.0.

Turn listings into contacts

For every listing with a website, scrape emails from that website. Skip anything with no site. Report how many credits you used.

Verify before you send

Verify each email you found and drop anything that isn't deliverable.

Example prompts

Ask your clientWhat you get back
”Google Maps listings for dentists in Austin”Business listings for that query
”Same search with reviews, ranked by rating”Listings plus review data per place
”Build me a list of Austin dentists with contact emails”Chains scrape_emails_from_website per website
”Find the owner’s LinkedIn for each of these”Chains find_people_within_company on the domain

Best prompting practices

  • Put the geography in the query and in location. “Dentists in Austin” plus location: "Austin, TX" is more reliable than either alone.
  • Only turn on include_reviews when you will use them. It scrapes each place detail page, so the call takes noticeably longer on a large max_results.
  • Set max_results to the size of the list you actually want. The default of 10 is a sample, not a territory.
  • Run one city per call. “Dentists in Austin and Dallas” gives you a worse result set than two calls.
  • Chain, do not guess. Ask for emails to be scraped from the returned websites rather than letting your client invent info@ addresses.

Output

{ "query": "dentists in Austin", "listings": [ { "name": "Congress Ave Dental", "website": "https://congressavedental.com", "phone": "+1 512-555-0142", "rating": 4.7 } ] }

Credits and limits

0.3 credits per call, whatever max_results you set. Run check_credits (free) before a large batch.

Listings carry a website and a public phone number, not a named decision-maker. Budget for the follow-on calls: one scrape_emails_from_website per website at 0.5 credits each adds up faster than the listing call itself.


ToolUse it instead when
scrape_emails_from_websiteYou have the websites and need contact addresses — 0.5 credits
scrape_phones_from_websiteYou need office numbers from the site — 0.5 credits
find_companiesYou are building a B2B list on firmographics, not geography
enrich_organizationYou have the domain and want firmographics — 2 credits

Next steps


Keep learning

Two courses take these tools past the reference page — clustered by GTM job, then chained into workflows.