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Google Maps Contact Extract

OrganizationPopular
browser-act
google-maps-contact-extract

Extracts business contact details from Google Maps search results and place detail pages, then visits each business website to collect emails, phone numbers, and social media profiles (Facebook, Instagram, Twitter/X, LinkedIn, YouTube, TikTok, Pinterest, Discord). Use when user mentions Google Maps contact extraction, maps email scraper, business lead generation from Google Maps, find emails from maps, scrape Google Maps businesses, maps business contacts, get phone from Google Maps, social media from maps listing, competitor research from maps, local business contact list, maps data export, google maps scraper, extract contacts from google maps, find business email google, gmaps leads, maps email finder, or wants to replicate Google Maps business data extraction.

Overview

Publisherbrowser-act
Repositoryskills
Skill namegoogle-maps-contact-extract
Stars
5.9K
Forks
295
Bundled files
3
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by browser-act on GitHub. Read the source before you install it.

Installation

Install the Google Maps Contact Extract AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/browser-act/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/solutions/lead-generation/google-maps-contact-extract .claude/skills/google-maps-contact-extract
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Google Maps Contact Extract in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Google Maps Contact Extract on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Google Maps Contact Extract is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Google Maps — Contact Extractor

keyword + location → business list with name/address/phone/website + email/social media/contacts from each business's website

Language

All process output to user (progress updates, process notifications) follows the user's language.

Objective

Search Google Maps by keyword and location, collect place details from each result, visit each business's website to extract emails and social media profiles, and return a merged dataset replicating Google Maps Email Extractor functionality.

Prerequisites

  • For search: navigate to https://www.google.com/maps/search/{keyword}/@{lat},{lng},{zoom}z — the search results sidebar (feed) must be visible
  • For place detail: navigate to the individual place URL https://www.google.com/maps/place/?q=place_id:{place_id} — the place sidebar with name, address, phone must be visible
  • For website contact extraction: navigate to the business's website homepage
  • No login required for Google Maps or most business websites

Pre-execution Checks

1. Tool Readiness

If browser-act has been confirmed available in the current session → skip this step.

Invoke browser-act via Skill tool to load usage. If installation or configuration issues arise, follow its guidance to resolve then retry.

Capability Components

This Skill's operational boundary = what the user can manually do in their browser. It only reads data already displayed to the user on the page, never bypassing authentication or access controls. JS code is encapsulated in Python files under the scripts/ directory, invoked via eval "$(python scripts/xxx.py {params})". It is recommended to use the bash tool for execution. Working directory: all python scripts/ commands must be run from the Skill's root directory (the directory containing SKILL.md and scripts/). Use cd {skill-directory} before running batch scripts, or use absolute paths: python {absolute-path-to-scripts}/xxx.py.

DOM: Search results list — extract business cards from Google Maps search feed

Prerequisite: navigate to and wait for Google Maps search results to load, then extract all visible business cards.

navigate https://www.google.com/maps/search/{keyword}/@{lat},{lng},{zoom}z
wait stable
eval "$(python scripts/search-places.py '{keyword}' --max {max_count})"

Parameters:

  • {keyword}: search term, e.g. coffee shops
  • --max: maximum number of places to extract, default 20
  • {lat},{lng}: center coordinates, e.g. 40.7580,-73.9855
  • {zoom}: zoom level, e.g. 14

Output example:

json
{
  "keyword": "coffee shops",
  "count": 20,
  "places": [
    {
      "name": "Blue Dove Coffee",
      "rating": 4.8,
      "review_count": "292",
      "category": "Coffee shop",
      "price_range": null,
      "phone": null,
      "open_status": "Closed · Opens 7 AM",
      "place_id": "0xa5922b78cc420fb1:0x535506dc9cdb2cec",
      "lat": 40.7368708,
      "lng": -73.9909297,
      "maps_url": "https://www.google.com/maps/place/Blue+Dove+Coffee/data=..."
    }
  ]
}

Pagination: Google Maps loads ~20 results per view. Scroll down in the results panel to trigger loading of additional results, then re-run the extraction script. Repeat until desired count is reached.

scroll down --amount 3000
wait stable
eval "$(python scripts/search-places.py '{keyword}' --max {total_count})"

DOM: Place detail — extract full business info from a Google Maps place page

Prerequisite: navigate to the place page and wait for the sidebar to load with name, address, and phone visible.

navigate https://www.google.com/maps/place/?q=place_id:{place_id}
wait stable
wait --selector "h1" --state visible --timeout 15000
eval "$(python scripts/place-detail.py)"

Alternatively, navigate directly using the maps_url returned from the search results component.

Output example:

json
{
  "place_id": "0xa5922b78cc420fb1:0x535506dc9cdb2cec",
  "name": "Blue Dove Coffee",
  "rating": 4.8,
  "review_count": 292,
  "category": "Coffee shop",
  "address": "33 Union Square W, New York, NY 10003",
  "located_in": null,
  "phone": "(646) 939-0937",
  "website": "https://www.bluedovecoffee.com/",
  "menu_url": "https://order.dripos.com/Blue-Dove-Coffee",
  "price_range": "$1–10",
  "coordinates": { "lat": 40.7368708, "lng": -73.9909297 },
  "hours": [
    "Monday7 AM–5 PM",
    "Tuesday7 AM–5 PM",
    "Wednesday7 AM–5 PM",
    "Thursday7 AM–5 PM",
    "Friday7 AM–5 PM",
    "Saturday7 AM–5 PM",
    "Sunday7 AM–4 PM"
  ],
  "service_options": ["Serves dine-in", "Offers takeout", "Offers delivery"],
  "amenities": ["Has wheelchair accessible entrance", "Accepts credit cards", "Accepts NFC mobile payments"],
  "maps_url": "https://www.google.com/maps/place/..."
}

DOM: Website contacts — extract emails, phones, social media from a business website

Prerequisite: navigate to the business website homepage.

navigate {website_url}
wait stable
eval "$(python scripts/extract-contacts.py --depth shallow)"

For deeper extraction (also scans contact/about subpages), use --depth deep. After running with --depth deep, check contact_subpages in the output, then navigate to each and re-run:

navigate {subpage_url}
wait stable
eval "$(python scripts/extract-contacts.py --depth shallow)"

Parameters:

  • --depth: shallow (homepage only, default) or deep (also discovers and lists contact/about subpage URLs)

Output example:

json
{
  "source_url": "https://www.bluedovecoffee.com/",
  "emails": ["support@bluedovecoffee.com", "careers@bluedovecoffee.com", "orders@bluedovecoffee.com"],
  "phone_numbers": [],
  "social_media": {
    "facebook": ["https://www.facebook.com/people/Blue-Dove-Coffee/100094867009022"],
    "instagram": ["https://www.instagram.com/bluedovecoffee"],
    "tiktok": ["https://www.tiktok.com/@bluedovecoffee"]
  },
  "contact_subpages": []
}

Composite: Full pipeline — search + place details + website contacts

Complete flow replicating Google Maps Email Extractor:

  1. Navigate to Google Maps search:

    navigate https://www.google.com/maps/search/{keyword}/@{lat},{lng},{zoom}z
    wait stable
    eval "$(python scripts/search-places.py '{keyword}' --max {max_count})"

    Save list of places (especially name, maps_url, place_id).

  2. For each place: navigate to place detail page and extract full info:

    navigate {maps_url}
    wait stable
    wait --selector "h1" --state visible --timeout 15000
    eval "$(python scripts/place-detail.py)"

    Collect website, phone, address, hours, rating, etc.

  3. For each place with a website value: extract contacts from the website:

    navigate {website}
    wait stable
    eval "$(python scripts/extract-contacts.py --depth deep)"

    For each URL in contact_subpages, navigate and extract again to find additional emails.

  4. Merge results: join by place_id or name. Final record per business:

    json
    {
      "name": "Blue Dove Coffee",
      "address": "33 Union Square W, New York, NY 10003",
      "phone": "(646) 939-0937",
      "website": "https://www.bluedovecoffee.com/",
      "rating": 4.8,
      "review_count": 292,
      "category": "Coffee shop",
      "coordinates": { "lat": 40.7368708, "lng": -73.9909297 },
      "hours": ["Monday7 AM–5 PM", "..."],
      "service_options": ["Serves dine-in", "Offers takeout"],
      "emails": ["support@bluedovecoffee.com"],
      "social_media": {
        "instagram": ["https://www.instagram.com/bluedovecoffee"],
        "tiktok": ["https://www.tiktok.com/@bluedovecoffee"]
      }
    }

Pagination

DOM Pagination: Google Maps search loads ~20 results initially. Scroll down in the sidebar:

scroll down --amount 3000
wait stable
eval "$(python scripts/search-places.py '{keyword}' --max {total_count})"

Repeat until the desired number of results is reached. Termination: Google Maps typically shows up to ~120 results per search; the sidebar will show "You've reached the end of the results" or stop loading new items.

Success Criteria

  • places.count >= 1 from search results extraction
  • Place detail returns name != null AND (address != null OR phone != null)
  • Website contact extraction returns emails.length + phone_numbers.length + Object.keys(social_media).length >= 0 (no contacts = valid result for businesses without public contact info)

Known Limitations

  • Google Maps search results are limited to approximately 120 businesses per search query; to get more, use more specific sub-area searches
  • Phone numbers on the Google Maps search list card are not always shown; place-detail.py on the individual place page is more reliable
  • Website contact extraction depends on the business's website structure; sites using image-based emails or obfuscated text will return no emails
  • Some businesses do not have a website listed on Google Maps; those cannot be enriched with contact data
  • Google Maps may throttle requests if too many place pages are navigated in rapid succession; add 1–2 second delays between place navigations in batch scripts

Execution Efficiency

  • Batch orchestration: Write a bash script that loops through the pipeline steps in a single session. Add a 1–2 second sleep between each place detail navigation to avoid triggering anti-scraping. Example:
    bash
    for place_url in "${place_urls[@]}"; do
      browser-act --session gmaps-s1 navigate "$place_url"
      browser-act --session gmaps-s1 wait stable
      browser-act --session gmaps-s1 eval "$(python scripts/place-detail.py)"
      sleep 1.5
    done
  • Test before batch execution: Test with 2–3 places before running the full batch
  • Error resumption: Save each place's result to a JSON file immediately after extraction; on failure, skip already-saved places by checking if the file exists
  • Multiple sessions for throughput: Open 2–3 parallel stealth browser sessions and distribute places across them; each session has an independent fingerprint

Experience Notes

Path: {working-directory}/browser-act-skill-forge-memories/google-maps-contact-extract.memory.md

Before execution: If the file exists, read it first — it records unexpected situations encountered during past executions (e.g., a strategy has become ineffective); adjust strategy order accordingly.

After execution: If an unexpected situation is encountered (strategy became ineffective, page redesigned, anti-scraping upgraded, better path discovered), append a line: {YYYY-MM-DD}: {what happened} → {conclusion}

Normal execution does not write to the file.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Google Maps Contact Extract AI skill do?

Extracts business contact details from Google Maps search results and place detail pages, then visits each business website to collect emails, phone numbers, and social media profiles (Facebook, Instagram, Twitter/X, LinkedIn, YouTube, TikTok, Pinterest, Discord). Use when user mentions Google Maps contact extraction, maps email scraper, business lead generation from Google Maps, find emails from maps, scrape Google Maps businesses, maps business contacts, get phone from Google Maps, social media from maps listing, competitor research from maps, local business contact list, maps data export...

Why use Google Maps Contact Extract on TypingMind?

Because you install it once and use it with any model. Google Maps Contact Extract is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Google Maps Contact Extract in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/browser-act/skills/tree/main/solutions/lead-generation/google-maps-contact-extract. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Google Maps Contact Extract?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Google Maps Contact Extract?

As many as you like. As long as a model supports skills, you can use Google Maps Contact Extract with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Google Maps Contact Extract AI skill free?

Yes. It is published on GitHub by browser-act under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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