# Website Tech Stack Detector — Identify Frameworks and CMS Used (`knotless_cadence/website-tech-stack-detector`) Actor Detect technologies used by any website — frameworks, CMS, analytics, CDN, hosting. Bulk-scan competitor sites. Perfect for sales intelligence and market research. Custom pipeline: $100 pilot, spinov001@gmail.com - **URL**: https://apify.com/knotless\_cadence/website-tech-stack-detector.md - **Developed by:** [Alex](https://apify.com/knotless_cadence) (community) - **Categories:** SEO tools, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## 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 Detector Detect the technology stack of any website — identify 60+ technologies including CMS, frameworks, analytics, hosting, payments, and more. Just enter a URL and get a categorized breakdown in seconds. ### Features - **60+ technologies detected** — CMS, JS frameworks, analytics, CDN/hosting, payment systems, chat widgets, email platforms, e-commerce, and security tools - **Categorized results** — technologies organized into 9 categories: CMS, framework, analytics, hosting, payment, chat, email, e-commerce, security - **Bulk analysis** — scan hundreds of websites in a single run - **Meta data extraction** — page title, description, Open Graph image, server info, scripts count, stylesheets count - **Header analysis** — detects server software and infrastructure from HTTP response headers - **No API keys needed** — works out of the box, just enter URLs ### Output Example ```json { "url": "https://stripe.com", "title": "Stripe | Financial Infrastructure for the Internet", "description": "Stripe powers online and in-person payment processing...", "server": "cloudflare", "technologiesCount": 8, "technologies": ["Next.js", "React", "Cloudflare", "Google Analytics", "Segment", "Stripe", "Google Fonts", "Sentry"], "categories": { "cms": [], "framework": ["Next.js", "React"], "analytics": ["Google Analytics", "Segment"], "hosting": ["Cloudflare"], "payment": ["Stripe"], "chat": [], "email": [], "ecommerce": [], "security": [], "other": ["Google Fonts", "Sentry"] }, "scriptsCount": 12, "stylesheetsCount": 3, "scrapedAt": "2026-03-18T12:00:00.000Z" } ```` ### Use Cases - **Competitive intelligence** — discover what technologies your competitors use for their websites - **Sales prospecting** — find companies using specific tech stacks (e.g., all Shopify stores, all WordPress sites) - **Market research** — analyze technology adoption trends across hundreds of websites in your industry - **Lead qualification** — identify potential customers by their current tech stack (e.g., companies using outdated CMS) - **Security audits** — detect outdated libraries, missing security headers, and vulnerable technologies ### Input Parameters | Parameter | Type | Default | Description | |-----------|------|---------|-------------| | `urls` | Array | `["https://example.com"]` | List of website URLs to analyze (with or without https://) | ### Cost Estimation - \~$0.25 per 100 websites analyzed - Processes ~10 websites per second - Free tier: up to 50 websites with Apify free plan ### FAQ **Q: What technologies can it detect?** A: Over 60 technologies across 9 categories — including WordPress, Shopify, React, Next.js, Vue.js, Angular, Google Analytics, Cloudflare, Vercel, Stripe, Intercom, Zendesk, Tailwind CSS, and many more. **Q: How accurate is the detection?** A: Detection is based on HTML source code analysis and HTTP header inspection. Accuracy is 90%+ for technologies that leave visible footprints. Some server-side technologies may not be detectable from the frontend. **Q: Can I scan thousands of URLs at once?** A: Yes. The scraper runs with 10 concurrent requests and can process thousands of URLs in a single run. Just provide your URL list as input. # Actor input Schema ## `urls` (type: `array`): List of website URLs to analyze (e.g., 'stripe.com', 'https://github.com') ## Actor input object example ```json { "urls": [ "https://stripe.com", "https://github.com", "https://vercel.com" ] } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "urls": [ "https://stripe.com", "https://github.com", "https://vercel.com" ] }; // Run the Actor and wait for it to finish const run = await client.actor("knotless_cadence/website-tech-stack-detector").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${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 = { "urls": [ "https://stripe.com", "https://github.com", "https://vercel.com", ] } # Run the Actor and wait for it to finish run = client.actor("knotless_cadence/website-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 '{ "urls": [ "https://stripe.com", "https://github.com", "https://vercel.com" ] }' | apify call knotless_cadence/website-tech-stack-detector --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=knotless_cadence/website-tech-stack-detector", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Website Tech Stack Detector — Identify Frameworks and CMS Used", "description": "Detect technologies used by any website — frameworks, CMS, analytics, CDN, hosting. Bulk-scan competitor sites. Perfect for sales intelligence and market research. Custom pipeline: $100 pilot, spinov001@gmail.com", "version": "1.0", "x-build-id": "tjeqaW9LIwuKTkKeK" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/knotless_cadence~website-tech-stack-detector/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-knotless_cadence-website-tech-stack-detector", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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/knotless_cadence~website-tech-stack-detector/runs": { "post": { "operationId": "runs-sync-knotless_cadence-website-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/knotless_cadence~website-tech-stack-detector/run-sync": { "post": { "operationId": "run-sync-knotless_cadence-website-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": [ "urls" ], "properties": { "urls": { "title": "Website URLs", "type": "array", "description": "List of website URLs to analyze (e.g., 'stripe.com', 'https://github.com')", "default": [ "https://example.com" ], "items": { "type": "string" } } } }, "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 } } } } } } } } } } ```