# Website Tech Stack Detector - Signals & Alerts (`nicolas_izquierdo/tech-stack-detector`) Actor Detect the technology stack behind any list of websites: CMS, ecommerce, analytics, chat, payments, JS frameworks, CDN and more. Diff mode flags when a target company ADOPTS or DROPS a tool - schedule it and turn tech changes into B2B buying signals. Uses only public homepage markup and headers. - **URL**: https://apify.com/nicolas\_izquierdo/tech-stack-detector.md - **Developed by:** [Nicolas Izquierdo](https://apify.com/nicolas_izquierdo) (community) - **Categories:** Automation, Developer tools, Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $3.00 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Website Tech Stack Detector — Signals & Alerts **See exactly what any company runs its website on — and get pinged the day they switch.** Feed this Actor a list of domains and it tells you the technology behind each one: CMS, ecommerce platform, analytics, chat widget, payment provider, JS framework, CDN, marketing automation and more — ~110 technologies across 20 categories. Turn on **diff mode**, schedule it daily, and it only reports a site when it **adopts or drops** a tool. That change *is* the B2B buying signal. BuiltWith and Wappalyzer sell "companies that use technology X" lists for $295–995/month. This does the same detection on your own target list, on your schedule, for cents — with data you own. ### Why it's different Most Apify tech scrapers dump raw HTML. This one gives you a **clean, categorized stack per site plus change tracking** — the difference between "here's a page" and "here's a qualified lead who just installed Intercom." - **Official page markup only.** It reads the public homepage HTML and response headers — the same signals Wappalyzer, BuiltWith and your browser's dev tools use. No proxies, no logins, no ToS-risky scraping. - **Diff mode = sales signals.** `newTech` / `removedTech` per site. "Target account started using Shopify Plus" or "dropped Zendesk for Intercom" → a reason to reach out today. - **Evidence included.** Every detection ships with the exact marker that triggered it, so you can trust (and audit) the result. ### Use cases - **B2B sales & lead gen:** filter your prospect list to "uses Stripe" / "runs on Shopify" / "just added a chat widget," then sell the matching integration or service. - **Competitive intelligence:** watch competitors' stacks and get alerted when they change vendors. - **Agencies:** qualify inbound by platform (WordPress vs Webflow vs custom) before the first call. - **Investors/analysts:** tech adoption as an alt-data signal across a portfolio of companies. - **Partnerships:** find every site already running a tool that complements yours. ### Detected categories CMS · Ecommerce · Analytics · Tag managers · Advertising / pixels · Chat & support · Marketing automation · CRM · Payments · JS frameworks · CDN & hosting · Web servers · A/B testing · Error monitoring · Consent & privacy (CMP) · CDP · Email & forms · Video · Fonts & UI · Search ### Input ```json { "domains": ["stripe.com", "notion.so", "shopify.com"], "newTechOnly": false, "trackChanges": true, "computeSignals": true } ```` | Parameter | Type | Description | |---|---|---| | `domains` | Array (required) | Domains or URLs to analyze. `stripe.com`, `https://notion.so`, etc. One homepage fetched per entry. | | `categories` | Array | Restrict detection to specific categories. Empty = detect everything. | | `newTechOnly` | Boolean | Diff mode: only output sites whose stack changed since the last run. First run primes the memory. | | `trackChanges` | Boolean | Remember each site's stack between runs and fill `newTech` / `removedTech`. Default `true`. | | `onlyDetected` | Boolean | Skip rows for sites that couldn't be fetched (timeouts, blocks). | | `computeSignals` | Boolean | Append one run-summary item: totals by category, top technologies, share using chat / payments / analytics. | | `maxConcurrency` | Integer | Sites fetched in parallel (1–20, default 5). | ### Output One record per site: ```json { "type": "site", "domain": "stripe.com", "url": "https://stripe.com/", "statusCode": 200, "title": "Stripe | Financial Infrastructure...", "server": "nginx", "technologies": [ { "name": "Stripe", "category": "Payments", "confidence": "high", "evidence": "html: js.stripe.com/v3/" }, { "name": "Cloudflare", "category": "CDN & hosting", "confidence": "high", "evidence": "header cf-ray: 80a1..." } ], "techByCategory": { "Payments": ["Stripe"], "CDN & hosting": ["Cloudflare"] }, "techCount": 2, "newTech": ["Stripe"], "removedTech": [], "isNew": false, "scrapedAt": "2026-07-07T12:00:00.000Z" } ``` Plus one `run_signals` summary per run (unless disabled). ### Scheduling for alerts Set `newTechOnly: true`, schedule the Actor daily, and connect a Slack / email / webhook integration. You'll only hear about a domain when its stack actually changes — a lightweight, always-on competitor-and-prospect radar. Runs cost cents because there are no proxies and only the homepage is fetched. ### Notes & limits - Detection is based on the homepage only. Tools loaded exclusively on deeper pages (e.g. a checkout-only payment SDK) may not appear until v1.1 adds optional sub-page crawling. - Presence, not version: it reports *that* a technology is used, not which version. - Sites that hard-block bots or render everything client-side after load may expose fewer markers. ### FAQ **Is this allowed?** It only reads public homepage markup and HTTP headers — the same data your browser receives. No authentication, no proxies, no private data. **How accurate is it?** Signatures are the documented, stable fingerprints used across the industry. Each hit includes the evidence so you can verify it yourself. High-confidence markers are vendor-specific; medium-confidence ones are heuristic. **Part of a suite.** Pair it with our [ATS Jobs Scraper](https://apify.com/nicolas_izquierdo/ats-jobs-scraper) (hiring signals) and [Mentions Monitor](https://apify.com/nicolas_izquierdo/mentions-monitor) (conversation signals) for a full B2B signal stack: who's hiring, what they run, and where they're talked about. # Actor input Schema ## `domains` (type: `array`): Domains or URLs to analyze (one homepage fetched per entry). Accepts 'stripe.com', 'https://notion.so', etc. ## `categories` (type: `array`): Restrict detection to specific technology categories. Leave empty to detect everything. ## `newTechOnly` (type: `boolean`): Only output sites where the detected stack changed since the last run (tool adopted or dropped). Schedule daily + Slack/webhook = tech-change alerts. The first run primes the memory. ## `trackChanges` (type: `boolean`): Remember each site's stack between runs and populate the `newTech` and `removedTech` fields. ## `onlyDetected` (type: `boolean`): Do not output rows for sites that could not be fetched (timeouts, blocks, DNS errors). ## `computeSignals` (type: `boolean`): Append one summary item per run: totals by category, top technologies, and how many sites use chat / payments / analytics. ## `maxConcurrency` (type: `integer`): How many sites to fetch in parallel. ## Actor input object example ```json { "domains": [ "stripe.com", "notion.so", "basecamp.com" ], "categories": [], "newTechOnly": false, "trackChanges": true, "onlyDetected": false, "computeSignals": true, "maxConcurrency": 5 } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "domains": [ "stripe.com", "notion.so", "basecamp.com" ] }; // Run the Actor and wait for it to finish const run = await client.actor("nicolas_izquierdo/tech-stack-detector").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "domains": [ "stripe.com", "notion.so", "basecamp.com", ] } # Run the Actor and wait for it to finish run = client.actor("nicolas_izquierdo/tech-stack-detector").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "domains": [ "stripe.com", "notion.so", "basecamp.com" ] }' | apify call nicolas_izquierdo/tech-stack-detector --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=nicolas_izquierdo/tech-stack-detector", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Website Tech Stack Detector - Signals & Alerts", "description": "Detect the technology stack behind any list of websites: CMS, ecommerce, analytics, chat, payments, JS frameworks, CDN and more. Diff mode flags when a target company ADOPTS or DROPS a tool - schedule it and turn tech changes into B2B buying signals. Uses only public homepage markup and headers.", "version": "1.0", "x-build-id": "QaUoPhO4ysMKlumRX" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/nicolas_izquierdo~tech-stack-detector/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-nicolas_izquierdo-tech-stack-detector", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/nicolas_izquierdo~tech-stack-detector/runs": { "post": { "operationId": "runs-sync-nicolas_izquierdo-tech-stack-detector", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/nicolas_izquierdo~tech-stack-detector/run-sync": { "post": { "operationId": "run-sync-nicolas_izquierdo-tech-stack-detector", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "domains" ], "properties": { "domains": { "title": "Websites", "type": "array", "description": "Domains or URLs to analyze (one homepage fetched per entry). Accepts 'stripe.com', 'https://notion.so', etc.", "items": { "type": "string" } }, "categories": { "title": "Only these categories (optional)", "type": "array", "description": "Restrict detection to specific technology categories. Leave empty to detect everything.", "items": { "type": "string", "enum": [ "CMS", "Ecommerce", "Analytics", "Tag manager", "Advertising", "Chat & support", "Marketing automation", "CRM", "Payments", "JS framework", "CDN & hosting", "Web server", "A/B testing", "Error monitoring", "Consent & privacy", "CDP", "Email & forms", "Video", "Fonts & UI", "Search" ], "enumTitles": [ "CMS", "Ecommerce", "Analytics", "Tag manager", "Advertising / pixels", "Chat & support", "Marketing automation", "CRM", "Payments", "JS framework", "CDN & hosting", "Web server", "A/B testing", "Error monitoring", "Consent & privacy", "CDP", "Email & forms", "Video", "Fonts & UI", "Search" ] }, "default": [] }, "newTechOnly": { "title": "New / changed sites only (diff mode)", "type": "boolean", "description": "Only output sites where the detected stack changed since the last run (tool adopted or dropped). Schedule daily + Slack/webhook = tech-change alerts. The first run primes the memory.", "default": false }, "trackChanges": { "title": "Track stack changes across runs", "type": "boolean", "description": "Remember each site's stack between runs and populate the `newTech` and `removedTech` fields.", "default": true }, "onlyDetected": { "title": "Skip failed fetches", "type": "boolean", "description": "Do not output rows for sites that could not be fetched (timeouts, blocks, DNS errors).", "default": false }, "computeSignals": { "title": "Add a run summary signal", "type": "boolean", "description": "Append one summary item per run: totals by category, top technologies, and how many sites use chat / payments / analytics.", "default": true }, "maxConcurrency": { "title": "Max concurrent sites", "minimum": 1, "maximum": 20, "type": "integer", "description": "How many sites to fetch in parallel.", "default": 5 } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```