Google Maps Scraper Kit

A free, open-source Google Maps scraper for lead generation that runs on your own machine. Name a business type and a city. Get back an outreach-ready CSV with name, phone, email, website, category, address, rating and review count, plus Instagram, Facebook, LinkedIn, TikTok, YouTube and X links when the site shows them. Add --no-socials to skip those, or --no-website for the businesses that still need a site.

No Google Maps API key, no SaaS credits, no data leaving your computer. One command starts the engine, with or without Docker. Then run it from the terminal, or let Claude Code, Codex or Cursor drive it for you in plain English.

Goal	Start here
Get a lead list in the next 5 minutes	Quick start
Let an AI coding agent run the scrape	Use it with Claude Code or any agent
Scrape many keywords or cities in one job	Batch jobs
Know what you get and where it stops	What you get and Honest limits
Compare it with gosom, Apify, Outscraper and chat AIs	How it compares and the open-source comparison
Follow a worked recipe for dentists, roofers or restaurants	Guides and recipes

Sponsored by Swiftproxy and SerpApi. Paid placements; details below.

---

Quick start

Requires Python 3.9 or newer and Google Chrome (or Chromium, Edge or Brave). The engine and the scripts use the Python standard library by default. Optional website rendering adds Playwright (setup); the basic crawl needs no pip install. No browser installed? The first start downloads Chrome for Testing once, about 100 MB, checked against a pinned SHA-256.

Open a terminal (macOS: Terminal; Windows: PowerShell) and run these four lines:

git clone https://github.com/Mahanaicoach/google-maps-scraper-kit.git
cd google-maps-scraper-kit
python3 scripts/engine.py start
python3 scripts/scrape.py "coffee shops in Austin TX" 30.2672 -97.7431 --depth 2

Port 8080 taken? Run cp .env.example .env, set SCRAPER_PORT=8081 (any free port) in it, and start again. Then use that port wherever these docs say 8080.

On Windows, type py in place of python3. Stop the engine with python3 scripts/engine.py stop.

Prefer Docker? Replace the third line with docker compose up -d, with Docker Desktop installed and open. If the native engine is running, stop it first (python3 scripts/engine.py stop). The two keep separate job lists, so jobs started in one do not show in the other. The first run builds the engine image, about a minute. It is the same engine on the same port, so every other command stays the same.

Prefer clicking? http://localhost:8080 has a form; it returns the engine's raw CSV or JSON. Already running another copy of the kit on this machine? Set SCRAPER_PORT in .env first (SETUP §6, "second copy").

No coordinates handy? Let the Python CLI geocode the city:

python3 scripts/scrape.py "dentists in Denver CO" --city "Denver, CO" --depth 5

Each --depth step loads one more batch of about 20 places: --depth 2 returns about 40, --depth 5 up to about 100, near Google's cap of about 120 per search. Need the whole city? Add --grid 3:

python3 scripts/scrape.py "dentists in Denver CO" --city "Denver, CO" --grid 3

Want every listing, not just a grid's worth? --deep-scan (the ! option: slower) runs the grid, then splits every tile that came back at Google's cap into four sub-tiles one zoom level in, deduped:

python3 scripts/scrape.py "restaurants in Denver CO" --city "Denver, CO" --deep-scan

Example output

results-<short job id>.csv from the first command above (pass --out to name it yourself). Illustrative rows. The file also has six social columns after these eight (see below):

title	phone	emails	website	category	address	review_rating	review_count
Example Roasters	+1 512-555-0101	[email protected]	example.com	Coffee shop	100 Congress Ave, Austin, TX	4.7	312
Sample Espresso Bar	+1 512-555-0102	[email protected]	example.org	Cafe	200 S Lamar Blvd, Austin, TX	4.5	128

review_count works in headless mode; see Honest limits.

--browser-sites enables optional Playwright retries when HTTP finds no emails or social profile links. It renders JavaScript and shares the rendered homepage between both passes. Output adds website_fetch_status: http, rendered, blocked, timeout, budget_exhausted or error. See optional setup.

The social columns instagram, facebook, linkedin, tiktok, youtube and x come after the eight lead fields by default. --no-socials drops them. --tech adds fb_pixel, google_ads_tag, analytics, bing_ads, linkedin_insight, tiktok_pixel, cms, mobile_friendly and intent_score, and sorts the hottest leads first. --verify-emails adds email_host. --full keeps every raw column, including coordinates, place IDs, all categories, the week's opening hours and whether the place is open now.

Full walkthrough, platform notes and troubleshooting: SETUP.md.

---

Sponsored by

Swiftproxy - Residential proxies for Google Maps scraping

90M+ residential IPs across 220+ locations, rotating or static, over HTTP(S) and SOCKS5, so big Google Maps and multi-city jobs keep running. Use code PROXY90 for 10% off. Try Swiftproxy →

---

SerpApi - Google Maps API in JSON and Markdown

Access Google Maps listings, reviews, directions, and other public search data with SerpApi's Google Maps API, delivered as clean, structured JSON and Markdown. Try SerpApi →

---

Use it with Claude Code or any agent

The kit ships a Claude Code skill that teaches the agent to run scripts/scrape.py for every scrape, what the output holds, and the rate-limit and data-handling guardrails. It also works with Codex, Cursor and any other Agent Skills-compatible tool.

Option A: open the folder in Claude Code. The skill and four slash commands load automatically.

cd google-maps-scraper-kit
claude

Option B: install the skill into an agent you already use.

npx skills add mahanaicoach/google-maps-scraper-kit

This installs the skill file only. The engine and scripts/scrape.py ship with the kit, so the agent first asks you to install it (the Quick start) and then works from its folder. The slash commands come with Option A.

Then ask in plain language:

Scrape gyms in Miami and give me phones, emails and websites.

The agent checks the engine is up and starts it if not, runs scripts/scrape.py in the background (it creates, waits for and saves the job), and hands you a clean table of the 8 lead fields plus the file.

Slash command (Claude Code)	Action
/scrape <business> in <city, ST> [depth]	Run one scrape, return a clean table and CSV
/scrape-batch <keywords-file> [--city "City, ST"]	Run many queries as one job
/scrape-setup	Start the engine and run a health check
/scrape-jobs [list | delete <id>]	List or delete jobs

Plain requests trigger the skill too: "build me a lead list of plumbers in Phoenix". The skill scrapes Google Maps business listings only. It does not scrape social platforms directly.

---

What you get

8 lead fields by default	name, phone, email, website, category, address, rating, review count, then the six social columns (--no-socials drops them). The engine writes 36 raw columns plus categories; --full keeps them all.
Email extraction, on by default	After the Maps job, the script crawls every business website, 16 at a time: the homepage, then its contact and about pages if the homepage shows no email. It prints your found rate.
Beyond the 120 cap	--grid 3 splits the city into 3 x 3 map tiles, runs them one at a time and dedupes on place_id. --deep-scan (! slower) goes further: any tile that comes back at the cap is split into 4 sub-tiles one zoom level in, so dense districts are searched block by block.
Social enrichment, on by default	Finds Instagram, Facebook, LinkedIn, TikTok, YouTube and X profiles in code (HTTP + regex), reusing the homepage the email crawl already fetched. Zero AI tokens. --no-socials skips it.
Who already advertises	--tech spots a Meta Pixel, Google Ads tag, analytics, Bing Ads, LinkedIn Insight and TikTok pixels on each website, plus its platform (WordPress, Shopify, Wix…) and mobile support, then ranks leads by an intent_score from 0 to 100. Zero AI tokens.
Filters	--no-website (businesses that still need a site), --min-rating, --min-reviews, --has-phone, --has-email, --limit. --exclude earlier.csv skips the places you already have, so a weekly re-run returns only new leads.
Email checks	--verify-emails looks up each domain's MX record over DNS (no key), drops dead domains and labels the mail host (google_workspace, microsoft_365, other, none; blank when the row has no email).
Auto-geocoding	Type a city name. Coordinates are resolved for you via OpenStreetMap. Repeat --city to run several cities into one file.
Batch jobs	Many keywords, one job, one CSV. The engine lists a place found by several keywords once.

Measured, not estimated

Fresh install of v2.1.0 on 2026-11-01: a MacBook, the installed Chrome, no Docker, no proxies, home internet. Every number below is one run, reproducible with the command shown.

Command	Result	Wall time
scrape.py "coffee shops in Austin TX" 30.2672 -97.7431 --depth 2	40 places, 11 emails, 16 with a social profile	21 s
scrape.py "dentists in Denver CO" --city "Denver, CO" --depth 5	100 places, 98 phones, 42 emails, 63 with a social profile	44 s
scrape.py "restaurants in Manhattan NY" 40.7580 -73.9855 --depth 20 --no-email --no-socials	119 places (Google's cap)	34 s
scrape.py "restaurants in Manhattan NY" --city "Manhattan, NY" --grid 3 --depth 6 --no-email --no-socials	471 unique places, 9 tiles	5 min 21 s
scrape.py "roofing contractors in Phoenix AZ" --city "Phoenix, AZ" --depth 3 --tech --verify-emails --min-rating 4.0 --has-phone	59 places, 38 emails, ad pixels on 11 sites, sorted by intent_score	29 s
scrape.py "cafes in Lisbon" --city "Lisbon, Portugal" --depth 2 --lang pt --country pt --reviews 3 --full	40 places with 3 reviews, a star histogram, the week's hours and photo URLs each	37 s

Whole session: 2,068 places across 27 jobs in 21 minutes, no unusual traffic page. Your results depend on the city, the hour and your IP. Open-source alternatives, with sources: docs/best-google-maps-scrapers.md.

Batch jobs and the Python CLI

scripts/scrape.py is a standalone, dependency-free Python CLI: single queries, batches, geocoding, socials and CSV output. It works on macOS, Linux and Windows.

python3 scripts/scrape.py --keywords-file examples/queries.example.txt --city "Denver, CO"

One keyword per line. One job. One CSV.

---

Honest limits

• About 120 listings per search. Google Maps stops scrolling at roughly 120 results per search. That is Google's cap, not the kit's. --grid is the fix: it splits the city into N x N map tiles, runs one job per tile, and dedupes the results on place_id. Tiles run one at a time, so a grid is slower and more likely to trip rate limits than a single search. Each depth step adds a batch of about 20 places.
• Review counts come with a changed user agent. Google gives a browser whose user agent says HeadlessChrome its "limited view": no review counts, today's hours only, no reviews. So the engine's headless Chrome sends its own user agent with HeadlessChrome replaced by Chrome (same OS, same version, nothing else changed), and Google returns review_count, the week's open_hours and reviews_link. Google can still leave a field out; if every count is missing, --min-reviews warns and skips that filter. Review texts and the star histogram come with --reviews N (up to 5 per place, one page load each). Business photo URLs come in images (--full), with no extra page loads. Rather run a real window, with the agent unchanged? SETUP §3.
• Emails only when a business publishes one. The script reads the business homepage, then its contact and about pages. Listings with no site, or a site with no visible email, return an empty emails cell. Instagram bios are not read. Expect emails on a fraction of rows, not all of them.
• Rate limits are real. Heavy use without proxies can get your IP temporarily rate-limited by Google for minutes to hours. When Google answers with its unusual-traffic page, the engine waits and retries the keyword up to 2 times, then stops the job and keeps the rows found before that. Your Google account is not affected. See Responsible use.
• The web UI is a simple form for beginners. Up front are "What" (a business type) and "Where" (a city), and two options that are on by default: "Emails" and "Social profiles", under "Collect". Both boxes take only picks from their lists, and each pick becomes a tag you can remove: type a few letters, then pick. Text that is not in a list is refused, and Enter never starts a search. Three collapsed sections hold the rest: "Location and language", "Advanced options" and "Proxies". The job list shows each job's status with a progress bar (a review stage reads "reading reviews 7 of 20"), its times in your local time, and CSV, JSON and Delete buttons. Downloads are named after the search, for example . It downloads the raw CSV or JSON, and its email and social options read homepages only, so the scripts find more emails and return the clean lead fields. Its What and Where boxes take only picks from their lists: about 4,100 business types (the kit's 201 popular ones in , add a niche there, then Google's own category names) and about 168,000 cities from GeoNames, so a search never names a place or a type that does not exist. Each type is searched in each city, one job per city, with the map centred on that city. The page loads two static files from GitHub (), with no tracking: the sponsor box's from this repo (cached for a day), and Google's category names for the What box (cached for 30 days). Scraped data stays on your machine.

---

How it compares

	This kit	gosom/google-maps-scraper (open source, Go)	Asking a chat AI	Apify, Outscraper and other cloud scrapers
Cost	Free (MIT)	Free (MIT)	Free	Per-result credits or subscription
Install	Python 3.9+ and Chrome; Docker optional	Docker, or a Go toolchain	Account	Account and key
Where data goes	Stays on your machine	Stays on your machine	Provider's servers	Provider's servers
Rows per query	Whole city with --grid, deduped on place_id	Manual -grid-bbox	Close to zero	Whole city, billed per result
Emails	On by default: homepage, contact and about pages, MX check	-email flag, homepage	No	Often a paid add-on
Social profiles	On by default: Instagram, Facebook, LinkedIn, TikTok, YouTube, X	No	No	Often a paid add-on
Who already advertises	--tech: Meta Pixel, Google Ads, analytics, platform, intent_score	No	No	No
Reviews	--reviews 1-5 plus the star histogram	Up to about 300 per place	No	Yes
Output	Clean CSV, 8 lead fields plus socials; JSON	CSV, JSON, PostgreSQL	Chat text	CSV or JSON
Driven by an AI agent	Skill plus four slash commands	Skill (needs Docker and Node)	n/a	No

Facts about other tools come from their own README on 2026-11-01; the full comparison with six open-source repos is in docs/best-google-maps-scrapers.md.

Ask a chat AI to "scrape Google Maps" and it hits a consent wall and JavaScript-rendered pages, so you get close to zero structured rows. This kit runs a real headless scraping engine locally and gives the agent a precise operating manual for it.

---

Guides and recipes

One page per job, with the exact commands. Index: docs/README.md.

• Google Maps email scraper: how the kit finds business emails
• Google Maps scraper in Python: every CLI flag
• Google Maps scraper without an API key
• Scrape Google Maps leads with Claude Code
• Best open-source Google Maps scrapers on GitHub, compared
• Recipes: dentists, roofing contractors, restaurants

---

FAQ

What is the best free Google Maps scraper on GitHub? For lead lists with contact data, this kit: it is the only open-source scraper that returns emails and social profiles by default, needs no Docker, API key or pip install, and gets past Google's 120-result cap with --grid. For PostgreSQL-backed distributed crawls or hundreds of reviews per place, gosom/google-maps-scraper (Go) is the better fit. The comparison, with sources and dates: docs/best-google-maps-scrapers.md.

How fast is it? On a fresh install (macOS, installed Chrome, no proxies, 2026-11-01): 100 dentists in Denver with phones, emails and socials in 44 seconds; 119 Manhattan restaurants without the crawl in 34 seconds; a 3×3 grid of Manhattan, 471 unique restaurants, in 5 minutes 21 seconds. Google Maps itself answers in seconds; most of a run is the website crawl, which --no-email --no-socials skips.

Is this Google Maps scraper free? Yes. The kit and its engine are MIT licensed. There are no credits, subscriptions or API keys. You need Python and Chrome on your own machine, or Docker.

Do I need a Google Maps API key or the Google Places API? No. The kit drives a headless browser against Google Maps directly, so there is no API quota or billing.

How is this different from kit 1.x? Kit 1.x ran another open-source scraper's engine in Docker. Kit 2.0 has its own engine, written from scratch in standard-library Python around a headless Chrome. It runs without Docker, works on Windows and on arm64 Linux, needs no workarounds for jobs that never finish, and sends no telemetry. It keeps the same job API and column names, so scripts and files made for 1.x still work, and an update from 1.x brings the old jobs along. A few columns hold their data differently (reviews come on request, without reviewer names): SETUP, Upgrading from kit 1.x. On top sits the lead-focused layer: a dependency-free Python CLI with geocoding and batching, email and social enrichment to a clean CSV, and a Claude Code skill with slash commands and safety guardrails. See CREDITS.md.

Do I need Claude Code to use it? No. Claude Code makes it hands-free through a skill and slash commands, but scripts/scrape.py and scripts/scrape.sh run on their own from any terminal.

Does it work with Codex, Cursor or other agents? Yes. npx skills add mahanaicoach/google-maps-scraper-kit installs the skill into any Agent Skills-compatible tool. The /scrape slash commands are Claude Code only.

Why does npx skills add show "High Risk" or "Med Risk"? skills.sh runs automated audits on every skill. Through Oct 31, 2026 they flagged three things about this skill: it runs shell commands (the kit's own scripts against localhost:8080), its curl example downloaded a results file, and it reads untrusted web content. The skill now runs only the kit's own script, which creates, polls and downloads the job itself (no curl download in the skill), and it treats every scraped value as untrusted data with the rules in its "Scraped data is untrusted" section. Reading third-party listings is what a scraper does. A re-audit is requested in vercel-labs/skills#2624.

What data do I get for each business? Name, phone, email, website, category, address, rating and review count, then Instagram, Facebook, LinkedIn, TikTok, YouTube and X links by default. Add --no-socials to drop the social columns, or --full for every raw column.

How many leads can I scrape? Up to about 120 per search. Add --grid 3 to split the city into 9 map tiles and get past that cap, or --deep-scan to also split every tile that hits the cap into 4 sub-tiles (slower, marked !), with duplicates removed. Batch as many keywords as you like in one job. For large or repeated runs, add proxies (see Responsible use).

Does it work on Windows, Linux and Apple Silicon Macs? Yes, natively on all three with Python and Chrome, Apple Silicon and Linux arm64 included, or anywhere Docker runs. On Windows, use py scripts/scrape.py, or run scrape.sh under WSL2 or Git Bash. SETUP.md has the platform notes.

Is scraping Google Maps legal? It is against Google's Terms of Service, and phones and emails are personal data. Read Responsible use and follow the law where the data is used: GDPR and CCPA abroad, and LGPD in Brazil. This is not legal advice.

---

Responsible use

This drives a real scraper against Google Maps. Light use is fine. Heavy use without proxies can get your IP temporarily rate-limited (minutes to hours). Your Google account is not affected.

• Run one job at a time. Start at depth 5 and raise only when needed.
• Watch for block signals: failed jobs, empty results, or far fewer rows than an identical earlier run.
• Add proxies for large or repeated runs: --proxy http://user:pass@host:port on the script (repeatable), or the "proxies" array on the raw API. URL-encode special characters in the username or password. With several proxies the keywords take turns, and a keyword Google refuses, or whose proxy fails, is retried through the next one. SOCKS5 works only without a username and password. Proxy passwords show as *** in the API and the web UI and never reach the log. Sponsor Swiftproxy takes 10% off with code PROXY90:

  "proxies": ["http://user:pass@host1:port", "http://user:pass@host2:port"]
  

• Treat output as leads to verify, not a dataset to resell. Phones and emails are personal data: follow GDPR, CCPA, CAN-SPAM and, in Brazil, LGPD — including the lawful basis, the purpose and an opt-out before any outreach.

For large requests, the agent flags the risk and suggests proxies, then proceeds. It refuses only clearly abusive use.

---

Featured in

• Best Google Maps Scrapers on GitHub in 2026 (Tested) by Scrap.io

Star history

If this kit saved you an afternoon of copy-pasting, a star helps the next person find it.

google-maps-scraper-kit/
├── engine/                 the kit's own engine: Google Maps over Chrome DevTools, HTTP API, web UI
│   ├── serve.py            the engine server on 127.0.0.1:8080
│   └── test_engine.py      offline tests, no network, no Chrome
├── Dockerfile              the engine image: Python + Debian's Chromium, non-root
├── docker-compose.yml      runs that image on 127.0.0.1:8080
├── .env.example            config template
├── scripts/
│   ├── engine.py           start, stop, status or restart the engine without Docker; list or delete jobs
│   ├── scrape.py           Python CLI: single, batch, geocoding, socials, CSV
│   ├── scrape.sh           bash CLI: single query
│   ├── update.sh           one-command update of a clone or fork
│   ├── test_scrape.py      offline tests, no network: python3 scripts/test_scrape.py
│   └── test_update.sh      checks update.sh, no network: bash scripts/test_update.sh
├── docs/                   guides and recipes
├── examples/               sample job body and batch keyword list
├── .claude/
│   ├── settings.json       pre-approved local commands for hands-free runs
│   ├── commands/           /scrape, /scrape-batch, /scrape-setup, /scrape-jobs
│   └── skills/google-maps-scraper/SKILL.md
├── CLAUDE.md               project instructions for Claude Code
├── CREDITS.md              attribution and licenses
└── SETUP.md                full setup guide

Updating

The web UI shows a line under its title when a newer release is out, and python3 scripts/engine.py status prints one (both check GitHub's releases once a day; SCRAPER_NO_UPDATE_CHECK=1 in .env turns it off). Nothing updates by itself. Pull the latest fixes with one command. It works in a clone of this repo or of your fork, and it keeps your own commits:

bash scripts/update.sh

If the engine runs in Docker, the script rebuilds and restarts it so the new version takes effect. Without Docker, restart it yourself: python3 scripts/engine.py restart. Forked it on GitHub? Run git push afterwards, or click Sync fork on your fork's page.

On Windows without Git Bash, run the same update by hand:

git pull https://github.com/Mahanaicoach/google-maps-scraper-kit.git master
py scripts/engine.py restart

With Docker, run docker compose up -d --build --remove-orphans in place of the second line.

Coming from kit 1.x? The same command moves you to the own engine, and your old jobs and their CSVs appear in the new web UI. Details: SETUP.md, upgrading from 1.x.

Support

Found a bug? Open an issue with the command you ran and the error. Issues are for problems with the kit. Run your own scrapes with the quick start above; requests like "find me hotels in Hamburg" are closed without action. Contributions: CONTRIBUTING.md. Security reports: SECURITY.md.

License

Built by Mahan. MIT licensed. Third-party components: CREDITS.md.