# Tech Stack Analyzer | Detect CMS & Website Technologies (`andok/tech-stack-analyzer`) Actor Bulk scan websites to detect their CMS, frameworks, and server tech. Build targeted B2B lead lists based on competitor technographics (like Wappalyzer). - **URL**: https://apify.com/andok/tech-stack-analyzer.md - **Developed by:** [Andok](https://apify.com/andok) (community) - **Categories:** Business, Developer tools - **Stats:** 9 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $1.00 / 1,000 url analyzeds 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 Analyzer Detect the CMS, frameworks, and analytics any website uses -- without needing access or credentials. Whether you are profiling competitors, qualifying leads by platform, or auditing a migration target, bulk technology detection saves hours of manual inspection. Feed in hundreds of URLs and get structured results back in seconds via API or the Apify Console. ### Features - **CMS detection** — identifies WordPress, Shopify, Webflow, Ghost, Joomla, Drupal, and Magento from HTML footprints and meta tags - **Framework fingerprinting** — detects React, Next.js, Gatsby, Vue.js, Nuxt.js, Angular, and Express via DOM markers and headers - **Server identification** — reads `Server` and `X-Powered-By` headers to surface Nginx, Apache, Cloudflare, Vercel, and PHP - **Analytics tracking** — flags Google Analytics, Facebook Pixel, and Hotjar presence - **Bulk processing** — scan hundreds of URLs in a single run with configurable concurrency - **Structured output** — results are grouped into `cms`, `frameworks`, `server`, `analytics`, and a combined `technologies` array - **Pay-per-event billing** — you only pay for each URL analyzed, with automatic charge-limit enforcement ### Input | Field | Type | Required | Default | Description | |-------|------|----------|---------|-------------| | `urls` | `array` | Yes | — | List of URLs to analyze. Each URL is fetched and scanned for technology fingerprints. | | `timeoutSeconds` | `integer` | No | `15` | Maximum seconds to wait for each URL response before timing out. | | `concurrency` | `integer` | No | `10` | Number of URLs to process in parallel. Increase for large batches, decrease if you hit rate limits. | #### Input Example ```json { "urls": [ "https://crawlee.dev", "https://shopify.com", "https://wordpress.org" ], "timeoutSeconds": 15, "concurrency": 10 } ```` ### Output Each URL produces one dataset item containing categorized technology arrays and metadata about the request. - `inputUrl` (`string`) — the URL you submitted - `finalUrl` (`string`) — the URL after redirects - `status` (`number`) — HTTP status code - `cms` (`string[]`) — detected content management systems - `frameworks` (`string[]`) — detected frontend/backend frameworks - `server` (`string[]`) — detected server software and hosting platforms - `analytics` (`string[]`) — detected analytics and tracking tools - `technologies` (`string[]`) — combined list of all detected technologies - `error` (`string | null`) — error message if the URL could not be fetched #### Output Example ```json { "inputUrl": "https://crawlee.dev", "finalUrl": "https://crawlee.dev/", "status": 200, "cms": [], "frameworks": ["Next.js", "React"], "server": ["Vercel"], "analytics": ["Google Analytics"], "technologies": ["Next.js", "React", "Vercel", "Google Analytics"] } ``` ### Pricing | Event | Cost | |-------|------| | URL Analyzed | Pay-per-event (see actor pricing page) | The actor stops automatically when the per-run charge limit is reached, so you never overspend. ### Use Cases - **Competitive intelligence** — profile hundreds of competitor sites to understand their tech choices and identify trends - **Lead qualification** — filter prospects by platform (e.g., find all Shopify stores or WordPress sites in a list) - **Migration audits** — inventory the current tech stack before a replatforming project - **Market research** — map technology adoption across an industry vertical at scale - **Agency prospecting** — identify sites running outdated CMS versions as potential service leads - **Security reconnaissance** — detect exposed server headers and framework versions for vulnerability assessment ### Related Actors | Actor | What it adds | |-------|-------------| | [Web Page Asset Extractor](https://apify.com/andok/asset-extractor) | Lists every script and stylesheet the page loads — see the exact resources behind each detected technology | | [JSON-LD & Schema.org Extractor](https://apify.com/andok/jsonld-extractor) | Pulls structured data from the same pages — combine tech stack with schema markup for a full site profile | | [OpenGraph & Twitter Card Inspector](https://apify.com/andok/opengraph-inspector) | Checks social preview meta tags — pair with tech detection for a complete metadata audit | # Actor input Schema ## `urls` (type: `array`): List of website URLs to analyze. Each URL is fetched and scanned for CMS, framework, server, and analytics fingerprints. ## `timeoutSeconds` (type: `integer`): Maximum seconds to wait for each URL response. Increase for slow or geographically distant sites. ## `concurrency` (type: `integer`): Number of URLs to process in parallel. Higher values speed up large batches but may trigger rate limits on some hosts. ## Actor input object example ```json { "urls": [ "https://crawlee.dev" ], "timeoutSeconds": 15, "concurrency": 10 } ``` # Actor output Schema ## `results` (type: `string`): No description ## `resultsCsv` (type: `string`): No description ## `run` (type: `string`): No description # 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://crawlee.dev" ] }; // Run the Actor and wait for it to finish const run = await client.actor("andok/tech-stack-analyzer").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://crawlee.dev"] } # Run the Actor and wait for it to finish run = client.actor("andok/tech-stack-analyzer").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://crawlee.dev" ] }' | apify call andok/tech-stack-analyzer --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=andok/tech-stack-analyzer", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Tech Stack Analyzer | Detect CMS & Website Technologies", "description": "Bulk scan websites to detect their CMS, frameworks, and server tech. Build targeted B2B lead lists based on competitor technographics (like Wappalyzer).", "version": "1.0", "x-build-id": "GxFNtGQGy8R67zsXb" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/andok~tech-stack-analyzer/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-andok-tech-stack-analyzer", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/andok~tech-stack-analyzer/runs": { "post": { "operationId": "runs-sync-andok-tech-stack-analyzer", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/andok~tech-stack-analyzer/run-sync": { "post": { "operationId": "run-sync-andok-tech-stack-analyzer", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "urls": { "title": "URLs", "minItems": 1, "type": "array", "description": "List of website URLs to analyze. Each URL is fetched and scanned for CMS, framework, server, and analytics fingerprints.", "items": { "type": "string" } }, "timeoutSeconds": { "title": "Timeout (seconds)", "minimum": 1, "maximum": 120, "type": "integer", "description": "Maximum seconds to wait for each URL response. Increase for slow or geographically distant sites.", "default": 15 }, "concurrency": { "title": "Concurrency", "minimum": 1, "maximum": 50, "type": "integer", "description": "Number of URLs to process in parallel. Higher values speed up large batches but may trigger rate limits on some hosts.", "default": 10 } } }, "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 } } } } } } } } } } ```