Agent skill

Google Maps Contact Extract

by browser-act in browser-act/skills

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…

MITAuto-check passedMarketing & SEO

Install Google Maps Contact Extract

skills CLI
$ npx skills add browser-act/skills --skill google-maps-contact-extract -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install browser-act/skills google-maps-contact-extract --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/browser-act/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/solutions/lead-generation/google-maps-contact-extract .claude/skills/google-maps-contact-extract && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
google-maps-contact-extract
GitHub stars
6.1k
Used in
1 other repo
Token cost
~2.9k tokens
SKILL.md length
887 words
Files
4 (incl. scripts)
Skills in repo
87
Repo updated
First seen
Licence
MIT

At a glance

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…

  • Works in 4 steps: Navigate to Google Maps search → For each place: navigate to place detail… → For each place with a website value:… → …
  • User mentions Google Maps contact extraction
  • SKILL.md covers Language, Objective, Prerequisites and Pre-execution Checks, plus 6 more sections
  • Runs Python scripts from its folder; calls python; reaches google.com and bluedovecoffee.com

What it does

Google Maps Contact Extract is an agent skill from browser-act/skills. 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…

Its SKILL.md is about 2.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including scripts (for example `scripts/extract-contacts.py`, `scripts/place-detail.py` and `scripts/search-places.py`).

It sits in Marketing & SEO, covering Web scraping, Lead generation and Competitor analysis. It works with Google Maps Platform, Discord, Instagram and LinkedIn. The repository describes itself as: Browser automation CLI built for AI agents. Break through anti-bot walls, hand off to humans across platforms when stuck. Parallel multi-task execution, independent multi-session… The licence is MIT.

When your agent uses it

  • User mentions Google Maps contact extraction
  • Maps email scraper
  • Business lead generation from Google Maps
  • Find emails from maps

Example prompts

  • “Use the google-maps-contact-extract skill to extract business contact details from Google Maps search results and place detail pages, then visits…”
  • “/google-maps-contact-extract”

Requirements

  • Python 3

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. Navigate to Google Maps search
  2. For each place: navigate to place detail page and extract full info
  3. For each place with a website value: extract contacts from the website
  4. Merge results: join by place_id or name. Final record per business

What it can do on your machine

Read from SKILL.md and the folder at commit 11c057b. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 3 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • google.com
    • bluedovecoffee.com
    • instagram.com
    • tiktok.com
    • order.dripos.com
    • facebook.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Google Maps Contact Extract loads about 2.9k tokens when it runs. Until then it costs about 201 tokens; SKILL.md has 887 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~201
When it runs · the whole SKILL.md, loaded when a task matches
~2.9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from browser-act/skills at commit 11c057b, republished under its MIT licence (© browser-act). 887 words, ~2,867 tokens.

Download SKILL.mdSave it as .claude/skills/google-maps-contact-extract/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
google-maps-contact-extract
description
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.

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"]
      }
    }
Show full SKILL.md (376 more words)Show less

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.

© browser-act, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (scripts) in solutions/lead-generation/google-maps-contact-extract of browser-act/skills.

  • SKILL.md
  • scripts/extract-contacts.py
  • scripts/place-detail.py
  • scripts/search-places.py

Open the folder on GitHubat commit 11c057b

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in browser-act/skills, which our catalogue first saw on October 7, 2026.

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Questions about Google Maps Contact Extract

What does Google Maps Contact Extract 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…. Google Maps Contact Extract is an agent skill from browser-act/skills. 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).

When should I use Google Maps Contact Extract?

Google Maps Contact Extract fits situations like: user mentions Google Maps contact extraction; maps email scraper; business lead generation from Google Maps; find emails from maps.

How do I install Google Maps Contact Extract in Claude Code?

Run `npx skills add browser-act/skills --skill google-maps-contact-extract -a claude-code`. Or copy the skill folder (solutions/lead-generation/google-maps-contact-extract in browser-act/skills) into .claude/skills/google-maps-contact-extract in your project. Claude Code loads it when a task matches its description.

How do I install Google Maps Contact Extract in Codex?

Run `npx skills add browser-act/skills --skill google-maps-contact-extract -a codex`. Or copy the skill folder (solutions/lead-generation/google-maps-contact-extract in browser-act/skills) into .agents/skills/google-maps-contact-extract in your project. Codex loads it when a task matches its description.

Can I use Google Maps Contact Extract in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add browser-act/skills --skill google-maps-contact-extract -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/google-maps-contact-extract, .gemini/skills/google-maps-contact-extract, .github/skills/google-maps-contact-extract and .opencode/skills/google-maps-contact-extract in your project.

What does Google Maps Contact Extract need to run?

Going by SKILL.md and its folder, Google Maps Contact Extract needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.

Does Google Maps Contact Extract access the network?

SKILL.md names 6 domains. In commands or code: google.com, bluedovecoffee.com, instagram.com, tiktok.com, order.dripos.com and facebook.com; the agent is likely to contact these when it follows the instructions. This is read from the text; nothing was executed.

Is Google Maps Contact Extract safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Google Maps Contact Extract use?

Google Maps Contact Extract is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Google Maps Contact Extract use?

About 2.9k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Google Maps Contact Extract?

Skills that share tags, products or a category with Google Maps Contact Extract: Apify Multi-Platform Scraper (apify/agent-skills, 2.4k stars), Scrapecreators API (ScrapeCreators/social-media-research-skills, 3.3k stars), Social Publisher (affaan-m/ECC, 275k stars) and Caption Writer (stevenflanagan1/social-ai-team, 241 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Google Maps Contact Extract?

browser-act (a GitHub organization) maintains it in browser-act/skills, which has 6,114 GitHub stars. The repository holds 87 skills in this directory. The repository was last updated on August 24, 2026.

Source: browser-act/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.