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automationnation-mcp

by retracn
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Hybrid

Google Maps business leads

find_local_businesses
Read-only

Search Google Maps by business type and city to build local B2B sales lead lists with contact details, ratings, website data, lead scores, and optional AI outreach drafts.

Instructions

Find local businesses on Google Maps in any country, as sales leads. Returns name, category, address, phone, email (found on the business website), website, rating and review count, social profiles, opening-date estimate, unclaimed-listing flag and a lead score with reasons. Search any business type in any city, e.g. "dentist" in "Austin, TX". Filters for businesses without a website, recently opened businesses and review counts. Optional AI outreach drafts. About 1–3 minutes for 10 leads because it visits each website. Cost on your Apify account: $0.03 per lead ($0.024 on Gold).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
countryNoTwo-letter country code for the location, e.g. us, gb, ca, au, de.us
locationYesCity or area, e.g. "Austin, TX" or "Berlin, Germany". Add the state or country when a name is ambiguous.
find_emailsNoVisit each business website to find an email address. Slower, but most leads are useless without it.
max_resultsNoHow many businesses to return, 1–100. Each result is billed, so ask for what you need.
max_reviewsNoSkip businesses with more reviews than this, e.g. 30 to find newer businesses.
min_reviewsNoSkip businesses with fewer reviews than this.
business_typeYesWhat to search for on Google Maps, e.g. "dentist", "vegan restaurant" or "roofing contractor".
with_website_onlyNoOnly businesses that list a website.
opened_within_daysNoOnly businesses that opened within this many days; 30, 60 or 90 work best. 0 means any age.
without_website_onlyNoOnly businesses with no website (good prospects for web design and marketing services).
include_outreach_draftsNoAdd AI-written cold email, LinkedIn and SMS drafts for each lead.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.5/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations only cover the safety profile (readOnly, openWorld, not idempotent); the description adds the operational facts an agent actually needs — 1–3 minute runtime because each website is visited, per-lead billing at $0.03 ($0.024 Gold), and that max_results drives cost. That is substantive context beyond structured fields.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with purpose, then the return fields, then usage examples, then operational caveats. Four sentences, each carrying distinct information, with no filler or repetition of the title.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema and 11 parameters, the description compensates by enumerating the returned fields (name, category, address, phone, email, website, rating, review count, socials, opening-date estimate, unclaimed flag, lead score) and by disclosing cost and latency. Nothing an agent needs to call this correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so each of the 11 parameters is already documented. The description reinforces a few of them (email found on the website, no-website/recently-opened/review-count filters, AI outreach drafts) but adds no syntax, defaults, or constraints beyond what the schema provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource ('Find local businesses on Google Maps'), names the scope ('any country'), and implicitly distinguishes itself from the sibling find_uk_business_leads by covering global coverage rather than UK-only. An agent can route correctly without opening the schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides concrete invocation examples ("dentist" in "Austin, TX"), names the filter categories available, and discloses time/cost so the agent can judge whether to call it. It does not explicitly state when to prefer it over the UK-specific sibling or other search tools, so it falls short of full when/when-not guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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