Website Tech Stack Detector - Shopify, CMS, Ecommerce Platform

For lead-generation teams, agencies, sales ops and growth marketers who qualify leads by the technology a website runs ("Shopify stores using Klaviyo", "WordPress sites without GA4", "stores on Magento with no live chat"). Give it a list of websites and you get one row per site: the technologies detected on its home page - CMS, ecommerce platform, analytics, ad pixels, marketing tools, chat, payments, reviews, CDN, hosting, frameworks and consent tools - each with a confidence and the evidence that matched (script src contains cdn.shopify.com, meta generator WordPress 6.4, cookie _shopify_y), plus flat columns (cms, ecommerce, analytics, marketing, payments, chat, cdn, hosting, frameworks) ready to filter on.

Pay-per-result: $0.01 per site analysed - 1,000 sites = $10. A site is charged only when its home page was fetched, analysed and at least one technology matched. Sites with nothing detected, blocked, unreachable or disallowed in robots.txt are delivered so you can see why, and are never charged.

It works as a Shopify detector, CMS detector, ecommerce platform detector and analytics detector for a whole list of sites at once: a bulk tech lookup. It also finds Klaviyo stores.

Honest scope: this reads the home page only (one request, plus robots.txt) and matches 166 technologies chosen because lead lists actually filter on them, not the 7,000+ of the big databases. It does not run a browser, so tags that only exist after JavaScript runs can be missed. Every match shows its evidence so you can check it in the page source. See "How detection works, and its limits".

Tech lookup: quick start (1 minute)

1. Open the Input tab and paste website domains or URLs (one per line, or a whole spreadsheet column or CSV row at once).
2. Click Start, then export the dataset to CSV/Excel/JSON or pull it through the API shown below.

{
  "websites": ["plausible.io", "stumptowncoffee.com", "dauntbooks.co.uk"],
  "maxItems": 100
}

Other ways to give it your list: a link to a CSV/TXT file (websitesFileUrl, for example a Google Sheets "Publish to web" CSV link) or another Actor's dataset (datasetId, see "Enrich a Google Maps or contact-scraper dataset"). Messy input is fine: bare domains, https://www. URLs with paths, email addresses (their domain is used; Gmail, Outlook and other free-mail addresses are skipped), several per line, duplicates.

What it detects: CMS, ecommerce platform and analytics

166 technologies in these categories (the category of each match, and the key of categories):

Category	Technologies
CMS (CMS)	WordPress, Wix, Squarespace, Webflow, Drupal, Joomla, Ghost, HubSpot CMS, Framer, TYPO3
Ecommerce platforms (Ecommerce)	Shopify, WooCommerce, Magento (includes Adobe Commerce), BigCommerce, PrestaShop, Shopware, Squarespace Commerce, Ecwid, Salesforce Commerce Cloud, Snipcart
Analytics and tag managers (Analytics)	Google Analytics 4, Universal Analytics, Google Tag Manager, Plausible, Fathom, Matomo, Hotjar, Microsoft Clarity, Mixpanel, Segment, Amplitude, Heap, Adobe Analytics, Adobe Experience Platform Launch, Simple Analytics, Umami, PostHog, FullStory, Optimizely, VWO, Cloudflare Web Analytics, Vercel Analytics, Yandex Metrica
Ad pixels (Advertising)	Meta Pixel, TikTok Pixel, LinkedIn Insight Tag, Pinterest Tag, Google Ads, Google AdSense, Google Ad Manager, X (Twitter) Pixel, Snapchat Pixel, Reddit Pixel, Microsoft Advertising
Marketing and email (Marketing)	Klaviyo, Mailchimp, HubSpot, Marketo, ActiveCampaign, Omnisend, Brevo, ConvertKit, Attentive, MailerLite
Chat and support (Chat)	Intercom, Drift, Zendesk, Crisp, Tawk.to, LiveChat, Tidio, Gorgias, Freshchat, Olark, Help Scout Beacon
Payments (Payments)	Stripe, PayPal, Klarna, Afterpay, Shop Pay, Square, Braintree, Adyen, Amazon Pay, Affirm, Mollie, Paddle, Razorpay
Reviews (Reviews)	Trustpilot, Yotpo, Judge.me, Okendo, Reviews.io, Stamped.io, Loox
CDN (CDN)	Cloudflare, Fastly, Akamai, AWS CloudFront, Shopify CDN
Hosting (Hosting)	Vercel, Netlify, WP Engine, Kinsta, GitHub Pages, Heroku, Pantheon, Google Cloud
Security and bot protection (Security)	Imperva, reCAPTCHA, hCaptcha, Cloudflare Turnstile
JavaScript frameworks (JavaScript framework)	React, Next.js, Vue.js, Nuxt, Angular, AngularJS, Svelte, SvelteKit, Gatsby, Remix, Astro, Alpine.js, htmx
JavaScript libraries (JavaScript library)	jQuery, jQuery UI
UI frameworks (UI framework)	Bootstrap, Tailwind CSS
Back-end frameworks (Web framework)	ASP.NET, Express, Laravel, Ruby on Rails, Django
Web servers (Web server)	Nginx, Apache, LiteSpeed, Microsoft IIS
Languages (Programming language)	PHP
Cookie consent (Consent)	OneTrust, Cookiebot, CookieYes, Usercentrics, Termly, iubenda, Osano, Complianz
Search (Search)	Algolia
Fonts and icons (Fonts)	Font Awesome, Google Fonts, Adobe Fonts
Maps (Maps)	Google Maps
Video embeds (Video)	YouTube, Vimeo
Page builders (Page builder)	Elementor, Divi
SEO plugins (SEO)	Yoast SEO, Rank Math
Error and performance monitoring (Monitoring)	Sentry, New Relic, LogRocket
Scheduling and forms (Scheduling and forms)	Calendly
Public JavaScript CDNs (JavaScript CDN)	jsDelivr, cdnjs, unpkg, Google Hosted Libraries

The list is our own: every signature was written for this Actor from how each product announces itself on a home page. It does not copy any third-party fingerprint database.

Example output

One real result, from a captured copy of the stumptowncoffee.com home page:

{
  "inputUrl": "stumptowncoffee.com",
  "domain": "stumptowncoffee.com",
  "finalUrl": "https://www.stumptowncoffee.com/",
  "status": "ok",
  "statusReason": null,
  "technologyCount": 4,
  "technologies": [
    { "name": "Shopify", "category": "Ecommerce", "confidence": "high", "evidence": "meta shopify-digital-wallet tag present" },
    { "name": "Klaviyo", "category": "Marketing", "confidence": "high", "evidence": "inline script contains _learnq" },
    { "name": "Shop Pay", "category": "Payments", "confidence": "high", "evidence": "script src contains shopifycloud/shop-js" },
    { "name": "Shopify CDN", "category": "CDN", "confidence": "high", "evidence": "script src contains cdn.shopify.com" }
  ],
  "categories": {
    "Ecommerce": ["Shopify"],
    "Marketing": ["Klaviyo"],
    "Payments": ["Shop Pay"],
    "CDN": ["Shopify CDN"]
  },
  "cms": null,
  "ecommerce": "Shopify",
  "analytics": [],
  "marketing": ["Klaviyo"],
  "payments": ["Shop Pay"],
  "chat": [],
  "cdn": "Shopify CDN",
  "hosting": null,
  "frameworks": [],
  "changeType": null,
  "added": null,
  "removed": null,
  "checkedAt": "2026-10-09T12:00:00.000Z"
}

Field by field:

• status: ok (analysed, at least one technology matched: the only charged status), no-technologies-detected, blocked, unreachable or robots-disallowed. statusReason says why for anything but a clean ok.
• technologies: every match with its name, category, confidence (high or medium) and evidence.
• categories: the same technologies grouped, {category: [names]}.
• cms, ecommerce, cdn, hosting: the single best match of that kind, else null. analytics, marketing, payments, chat, frameworks: lists of names, empty when none.
• changeType, added, removed: change mode only (see "Track technology changes on a schedule"); null otherwise.
• source: only when you enrich a dataset (see below).

How detection works, and its limits

For each site the Actor sends one GET request for the home page (and reads robots.txt first). From that single response it looks at:

• the script sources, link tags and inline scripts in the HTML (JSON data blocks such as JSON-LD and __NEXT_DATA__ are not searched, they are data not code);
• the meta tags (for example generator) and distinctive HTML markup (comments, script bodies and style bodies are removed first, so a commented-out snippet is not a detection);
• the response headers (server, x-powered-by, cf-ray, x-vercel-id, ...) and the names of the cookies the server sets (never their values).

Each signature is graded: high for an unambiguous match (the product's own script host, a documented header, cookie or snippet), medium for weaker evidence (a generic file name, a class prefix). A technology implied by another (Next.js implies React, WooCommerce implies WordPress) is reported with evidence: "implied by Next.js". The Actor favours precision over recall: visible text such as "we use Shopify" is never a signal.

What this means for you:

• Home page only. A technology used only on checkout, product or app pages is not seen. No second page, sitemap, script file or stylesheet is ever requested.
• No browser. Tags injected by JavaScript after load (many tag-manager-injected pixels, consent-gated scripts, single-page apps that render everything client-side) can be missed. Google Tag Manager is reported when it is there, but the tags it injects are not.
• 166 technologies, not 7,000. A technology outside the list is simply not reported. The list is chosen for lead qualification, not completeness.
• Absence is not proof. ecommerce: null means "none of the known platforms was detected on the home page", not "this site sells nothing".
• Sites that block bots are reported as blocked; nothing is worked around.

Enrich a Google Maps or contact-scraper dataset

Google Maps scrapers give each business's website; this Actor tells you what that website runs. Hand it the dataset and every row's website is analysed, with the source row's fields (title, placeId, address, ...) copied into source so results join straight back.

{
  "datasetId": "YOUR_DATASET_ID",
  "maxItems": 500
}

Chain it automatically: in the source Actor's Integrations tab add this Actor and set datasetId to {{resource.defaultDatasetId}}, so every finished Google Maps run is enriched with no manual step. By hand: copy the dataset ID from the source run's Storage tab, or pick the dataset in the input form (it uses your own access: you never paste a token).

It reads the first website, websiteUrl, web, url, domain, homepage, companyWebsite, company_website or site column that has a value (set datasetWebsiteField to use another column). The output of our own Email & Contact Scraper works the same way (its domain column), so a lead list can go Google Maps, then contacts, then tech stack. Rows without a website, with a Google Maps or social media link instead of a website, or that repeat a website (a chain's branches share one result row) are skipped and listed with their row number in the INPUT_REPORT record.

Shopify detector: find Klaviyo stores

The flat columns are made for filtering. The Apify dataset API returns whole rows, so filter in your own code, a Make or Zapier step, or jq. Fetch only the columns you need with fields:

curl -s "https://api.apify.com/v2/datasets/DATASET_ID/items?token=$APIFY_TOKEN&clean=true&fields=domain,ecommerce,marketing" \
  | jq -r '.[] | select(.ecommerce == "Shopify" and (.marketing | index("Klaviyo"))) | .domain'

// Shopify stores that use Klaviyo, but no live chat
const hits = items.filter((r) => r.ecommerce === 'Shopify' && r.marketing.includes('Klaviyo') && r.chat.length === 0);

# WordPress sites without GA4 (and without a tag manager that might load it)
hits = [r["domain"] for r in items
        if r["cms"] == "WordPress"
        and "Google Analytics 4" not in r["analytics"]
        and "Google Tag Manager" not in r["analytics"]]

More recipes: Magento stores (ecommerce == "Magento"); sites on Stripe but not Klarna ("Stripe" in payments and "Klarna" not in payments); Next.js sites on Vercel ("Next.js" in frameworks and hosting == "Vercel"); sites with a cookie banner but no analytics (categories.Consent present, analytics empty); only confident matches (filter technologies on confidence == "high"). In the Console, the Tech stack columns dataset view shows the flat columns as one table. Leave out sites whose status is not ok when you only want analysed sites.

Track technology changes on a schedule

Turn on Only changed technologies (onlyChangedSinceLastRun) and run the Actor on a Schedule. The first run delivers every site once (changeType: "firstSeen") and remembers its technologies. Every later run delivers only the sites whose detected technology set changed, with added (what appeared) and removed (what disappeared); unchanged sites are not delivered and not charged.

{
  "websites": ["plausible.io", "stumptowncoffee.com"],
  "onlyChangedSinceLastRun": true
}

A changed row looks like "changeType": "changed", "added": ["Gorgias"], "removed": ["Mailchimp"]. A site that is down or blocks the request later keeps its last known technologies and is not reported again. Use it to hear when a prospect adopts or drops a tool (a competitor's, or yours): "just installed Klaviyo", "dropped Intercom".

Alerts to chat or phone (optional): fill in a Discord, Telegram, Slack, Microsoft Teams, Google Chat, ntfy, Pushover or generic JSON webhook destination in the Notifications section of the input, and each run sends one message per changed site, such as Tech change: example.com added Klaviyo, removed Mailchimp. Notifications are free, nothing is sent when nothing changed, and the first run (the baseline) sends nothing.

Input

Field	What it does
websites	Domains, URLs or emails, any messy list. Up to 10,000 per run.
websitesFileUrl	An https link to a CSV/TXT file (up to 5 MB and 20,000 lines), for example a published Google Sheet.
datasetId	Another Actor's dataset to enrich, with datasetWebsiteField and datasetPassthroughFields to pick columns.
outputFormat	full (default, every field) or compact (a smaller row for AI agents, see "Use with AI agents (MCP)"). Charging is identical.
maxItems	Hard cap on delivered rows, default 100, maximum 10,000. Also your cost cap.
maxConcurrency	Sites read at once, default 5, maximum 10. Each site still gets about one request per second.
onlyChangedSinceLastRun, stateStoreName	Change mode (see above).
Notification fields	Optional chat, phone and webhook destinations for changes.

Input details

The Store form and the MCP tool schema show a short description for each field (an AI agent sees only the first 500 characters of each); the longer rules are here.

• websites: Paste anything, one per line or a whole spreadsheet column or CSV row. Each entry may be a domain (plausible.io), a URL with a path, query or www, an email address (its domain is used; free-mail addresses such as gmail, outlook, yahoo, icloud, proton, gmx, web.de, mail.ru, qq, 163 or aol are skipped), or several of these on one line separated by commas, semicolons, spaces or tabs. Entries are de-duplicated by registrable domain (www.example.co.uk and example.co.uk are one company; the first one given is read). Entries that cannot be used are never an error: they are skipped and listed, with the reason, in the run status and in the INPUT_REPORT record of the run's key-value store. Only the home page of each site is fetched (one request, plus robots.txt); a path you give is ignored. Up to 10,000 websites per run.
• websitesFileUrl: For example a Google Sheets "Publish to web" CSV link (File > Share > Publish to web > "Comma-separated values (.csv)"), a Dropbox shared link or a GitHub "Raw" link. The file is downloaded once (at most 5 MB and 20,000 lines) and every cell is read exactly like an entry of websites; it is added to the websites you list and de-duplicated with them. The link must open without signing in. The file is your own input list, so robots.txt is not applied to downloading it; it is never requested from private or internal addresses. The websites themselves are still read politely, with robots.txt checked first.
• datasetId: The dataset is typically the default dataset of another Actor's run, for example a Google Maps scraper (Google Maps Scraper by Compass is one) or our Email & Contact Scraper. To chain it automatically, open the source Actor's Integrations tab, add this Actor and set the field to {{resource.defaultDatasetId}}; by hand, copy the dataset ID from the source run's Storage tab. It is read with this run's own access (the account that starts this Actor): you never give a token, and it must be a dataset that account can open. Up to 20,000 rows are read; rows without a website, with a Google Maps, social network or marketplace link instead of a website, with free-mail or invalid values, or that repeat a website are skipped and listed with their row number in INPUT_REPORT. It is added to websites and websitesFileUrl and de-duplicated with them. A link to the dataset in Console or the API is accepted too. source on every result row carries fields of the source row so results can be joined back.
• datasetWebsiteField: the column name is matched exactly as spelled. Left empty, the first non-empty of website, websiteUrl, web, url, domain, homepage, companyWebsite, company_website, site is used. A value that is a Google Maps, social network (Facebook, Instagram, LinkedIn, X, YouTube, TikTok, ...) or marketplace link is never read as a website, whichever column it is in.
• datasetPassthroughFields: left empty, title, placeId, address, city, countryCode, phone, categoryName, totalScore, reviewsCount and url are copied, whichever the row has. At most 15 columns and 2,000 characters per value (longer text is cut; a list or object is copied as JSON text). source also always has datasetRow (the row's number in the dataset, counting from 0), sourceRowCount (how many dataset rows had this website; a chain of branches shares one website) and otherRows (placeId or title of the other rows of the same website, at most 20); those three names are reserved. When several rows have the same website, the first row's columns are kept.
• maxItems: you are charged $0.01 only for a row whose home page was analysed and matched at least one technology. Rows for sites with no technology detected, blocked, unreachable or disallowed by robots.txt are delivered (so you can see why) and count toward this cap, but are not charged.
• maxConcurrency: each website only ever receives about one request per second (robots.txt, then the home page), so this never hammers a single site; a higher number just finishes a long list sooner. Keep the default unless you have thousands of sites.
• onlyChangedSinceLastRun: added lists what appeared (for example Klaviyo) and removed what disappeared (for example Mailchimp). The first run delivers every website and remembers it (changeType firstSeen); later runs deliver only what changed, and unchanged websites are not delivered or charged. A site that is blocked or down on a later run keeps its last known technologies and is not delivered.
• stateStoreName: only used in change mode; keeps each website's last technology set across scheduled runs. Leave the default unless several tasks must keep separate histories.

Output fields

inputUrl, domain, finalUrl, status, statusReason, technologyCount, technologies (each name, category, confidence, evidence), categories, cms, ecommerce, analytics, marketing, payments, chat, cdn, hosting, frameworks, changeType, added, removed, checkedAt and, for dataset runs, source. Field names are stable.

Data protection

The Actor reads the public home page every visitor can see. It stores no cookie values (only cookie names, to recognise technologies), collects no personal data, logs no page content, and requires no login. It identifies itself with its own User-Agent, respects robots.txt and never tries to get around a block, a login or a bot check.

Use with AI agents (MCP)

This Actor works as a tool for Claude, ChatGPT, Cursor and other MCP clients through Apify's MCP server. The only input a call needs is websites.

Claude Desktop (claude_desktop_config.json), with your own token from Apify Console > Settings > API & Integrations:

{
  "mcpServers": {
    "apify-tech-stack": {
      "command": "npx",
      "args": [
        "-y", "mcp-remote",
        "https://mcp.apify.com?tools=lukehunter/website-tech-stack-detector",
        "--header", "Authorization: Bearer ${APIFY_TOKEN}"
      ],
      "env": { "APIFY_TOKEN": "<YOUR_APIFY_TOKEN>" }
    }
  }
}

Clients that support OAuth (Claude.ai, VS Code) can connect with just the URL https://mcp.apify.com?tools=lukehunter/website-tech-stack-detector and sign in to Apify. Never paste a real token into a shared file or chat.

Example. You ask: "What ecommerce platform and marketing tools do stumptowncoffee.com and dauntbooks.co.uk use?" The agent calls the tool lukehunter--website-tech-stack-detector with:

{
  "websites": ["stumptowncoffee.com", "dauntbooks.co.uk"],
  "outputFormat": "compact",
  "maxItems": 10
}

outputFormat: "compact" returns, per site, the status, the technology count and the stack grouped by category, without the per-technology evidence strings, so the result fits an agent's context. It is charged exactly like the default "full" output: $0.01 per site where at least one technology is detected, nothing otherwise. Set maxItems to cap spend.

Pricing and cost control

$0.01 per site analysed (one site event). A row is charged only when the home page was fetched, analysed and matched at least one technology (status: ok).

Sites analysed	Cost
100	$1
1,000	$10
10,000	$100

Never charged: sites with no-technologies-detected, blocked, unreachable or robots-disallowed (they are delivered so you see why), sites that did not change in change mode, and notifications. Cost is capped by maxItems (default 100, so a default run costs at most $1) and by the spending limit you set on the run: the Actor never delivers a row your limit cannot pay for. Compute is cheap: a site costs a fraction of a cent of Apify platform usage on top of that, shown on your usage page.

Limitations

• Home page only: one GET per site, no deep crawl, no headless browser. Client-side-only tags and technologies used only on inner pages are not seen.
• 166 technologies. Anything outside the list is not reported. Detection is evidence-based, so a technology hidden behind a tag manager, a consent wall or a proxy that rewrites asset hosts can be missed or graded medium.
• No version numbers beyond what a site states in a generator meta tag (shown in the evidence).
• Sites that block bots, serve a bot-check page, forbid the home page in robots.txt, or are down are reported as such and not charged.
• Technologies are read from what the server sends to a plain, honestly identified client. A site may serve a different page to a real browser.

Use it from your code, Make, Zapier or n8n

Built for automated pipelines: small runs, stable field names, one row per item, and you pay only for rows actually delivered.

One API call that runs the Actor and returns the data (replace $APIFY_TOKEN with your token from Apify Console → Settings → Integrations):

curl -s -X POST "https://api.apify.com/v2/acts/lukehunter~website-tech-stack-detector/run-sync-get-dataset-items?token=$APIFY_TOKEN" \
  -H 'Content-Type: application/json' \
  -d '{"websites": ["plausible.io", "stumptowncoffee.com", "dauntbooks.co.uk"], "maxItems": 20, "maxConcurrency": 5}'

JavaScript (npm i apify-client):

import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('lukehunter~website-tech-stack-detector').call({
  "websites": [
    "plausible.io",
    "stumptowncoffee.com",
    "dauntbooks.co.uk"
  ],
  "maxItems": 20,
  "maxConcurrency": 5
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();

Python (pip install apify-client):

import os
from apify_client import ApifyClient
client = ApifyClient(os.environ['APIFY_TOKEN'])
run = client.actor('lukehunter~website-tech-stack-detector').call(run_input={"websites": ["plausible.io", "stumptowncoffee.com", "dauntbooks.co.uk"], "maxItems": 20, "maxConcurrency": 5})
items = client.dataset(run['defaultDatasetId']).list_items().items

Schedules, webhooks and no-code tools: save your input as a Task, add a Schedule (e.g. hourly or daily), and attach a webhook or one of the Integrations tab's connectors (Make, Zapier, n8n, Google Sheets, Slack) to push each run's results into your own system.

Only new items each run: set "onlyChangedSinceLastRun": true on a scheduled Task and every run after the first delivers, and charges for, only items it hasn't delivered before for that same input. That makes it a ready-made change feed.

Reliability: an automated test runs this Actor's parser against the live site every day, and failures are fixed fast.

Feedback: an honest rating on the Store page, good or bad, helps others decide if this Actor fits their needs. Missing a field or found a problem? Open an issue on the Actor page.

FAQ

Is this a full BuiltWith or Wappalyzer replacement?

No, and it does not claim to be. Those tools know thousands of technologies and some also crawl more pages or keep history. This Actor detects 166 popular technologies from the home page and shows the evidence for every match, for $0.01 per site and no subscription. If your lead filters are things like "Shopify + Klaviyo" or "WordPress without GA4", it covers them; if you need long-tail technologies, it does not.

Why does a match say confidence: medium?

Medium means the evidence is plausible but not unique to that product, for example a generic file name such as webflow.js or a class prefix. Filter on confidence == "high" when you want only unambiguous matches. The evidence string says exactly what matched.

Why was a site not charged?

Only status: ok rows are charged: the home page was analysed and at least one technology matched. no-technologies-detected (a JavaScript-only shell or a hand-built site), blocked, unreachable and robots-disallowed rows are free, and statusReason explains each.

Why is a technology I can see on the site not detected?

Usually because it is loaded after the page renders (by a tag manager or a script) or lives on an inner page. Only the home page's HTML, headers and cookie names are read. If the technology is in the page source of the home page and in the list, open an issue on the Actor page with the site and we will check the signature.

Does it detect which tags Google Tag Manager loads?

No. It reports Google Tag Manager when its container is on the page, but the tags GTM injects at runtime are not in the HTML.

Does it respect robots.txt and avoid blocks?

Yes. robots.txt is read first and a disallowed home page is never requested (status: robots-disallowed). A site that answers 401, 403 or 429 or shows a bot check is reported as blocked; nothing is retried from another angle, no proxy or changed identity is used.

Can I use a Google Sheet or a CSV as the input?

Yes. Use File > Share > Publish to web > Comma-separated values (.csv) in Google Sheets, paste the link into websitesFileUrl, and every cell is read like an entry of websites. The file is your own list, so robots.txt is not applied to downloading it.

Can I enrich the output of a Google Maps scraper?

Yes: give its dataset ID as datasetId, or add this Actor in the Google Maps scraper's Integrations tab with {{resource.defaultDatasetId}}. Each result carries the source row's fields in source so you can join it back.

How do I only hear about sites whose tech stack changed?

Turn on onlyChangedSinceLastRun, schedule the Actor, and optionally add a chat or phone destination under Notifications. See "Track technology changes on a schedule".

Does it return version numbers?

Only the ones a site declares itself in a generator meta tag, shown in the evidence (for example meta generator WordPress 6.4). It does not guess versions.

Related Actors

Other data tools from the same developer, built to the same standard: official or public sources, hard cost caps, and honest documentation of limits.

• Domain Email Provider Lookup: the email provider (Google Workspace, Microsoft 365, Zoho and more), MX, SPF and DMARC setup of any domain list, with provider-change alerts.
• French Company Leads: French companies (entreprises) from the official Sirene-based API, filtered by NAF code, department, headcount and creation date, with SIREN/SIRET, officers and new-company alerts.
• Poland KRS Company Lookup: Polish companies from the official KRS API by KRS number: NIP, REGON, address, share capital, PKD and the board as published, with optional VAT status.
• Website Contact Scraper: emails, phone numbers and social profile links from any list of company domains, with the page each came from and a changed-contacts-only mode for scheduled runs.
• Impressum Scraper: legal entity data from the imprint of any company website in Germany, Austria and Switzerland: legal name and form, managing directors, HRB/HRA or FN register, VAT id and address, with a changed-data-only mode for scheduled runs.
• Google Maps Email Extractor & Lead Enricher: emails, phones, social links, named people and the tech stack of every business in your Google Maps Scraper results, one enriched row per business, with filters such as only Shopify stores with an email.
• Federal Register Rule Effective-Date Radar: final federal rules about to take effect, with citations, dockets and urgency.
• UK Tenders Monitor: new UK public-sector tenders from Contracts Finder and Find a Tender, filtered by CPV code, value, region and buyer, with Slack, Discord and Telegram alerts.