# Tech Stack Analyzer - Detect Website Technologies (`artifact-machine/artifact-machine-tech-stack-analyzer`) Actor Detect frameworks, analytics, CDN, hosting, and CMS from any website. HTTP-only, no browser. - **URL**: https://apify.com/artifact-machine/artifact-machine-tech-stack-analyzer.md - **Developed by:** [The Artifact Machine](https://apify.com/artifact-machine) (community) - **Categories:** Developer tools, Marketing - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $0.50 / tech stack report 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 web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows. 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/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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 ## The Artifact Machine Tech Stack Analyzer A small artifact for detecting the technology stack behind any website — frameworks, analytics, CDN, hosting, CMS, and server info. No browser needed, just a single HTTP request. Pulled from The Artifact Machine: generated, tested, and cleaned up by a human. ### What It Detects - **Frameworks**: Next.js, React, Vue, Angular, Svelte, Nuxt, Gatsby, Astro, Remix, jQuery, Alpine.js, HTMX, and more - **CMS**: WordPress, Shopify, Squarespace, Wix, Webflow, Drupal, Joomla, HubSpot CMS - **Analytics**: Google Analytics, GTM, Facebook Pixel, Hotjar, HubSpot, Mixpanel, Amplitude, Matomo, Segment, Clarity, and more - **CDN**: Cloudflare, Fastly, Akamai, CloudFront, Vercel, Netlify - **Hosting**: Vercel, Netlify, GitHub Pages, Heroku, AWS, Cloudflare, DigitalOcean - **SSR/Edge**: Vercel Edge, Cloudflare Workers, AWS Lambda, Deno Deploy, Fastly Compute - **Server**: server header, x-powered-by, content language ### Best For - competitive research - sales prospecting (know a prospect's stack) - technology market research - website migration planning - agency client onboarding ### Input ```json { "url": "https://example.com" } ```` ### Output The Actor writes one dataset item and an `OUTPUT` key-value record with all detected technologies categorized. ### Limits - HTTP-only detection — some client-rendered frameworks may be missed on the first request. - Detection is based on HTML and HTTP header patterns, not JavaScript execution. - Some sites may block automated requests — the Actor uses a standard browser User-Agent. - Results are best-effort based on known pattern signatures. ### Pricing Use pay-per-event pricing. Suggested starting price: `$0.50` to `$1.00` per analysis. # Actor input Schema ## `url` (type: `string`): The URL to analyze. If no scheme is provided, https:// is assumed. ## Actor input object example ```json { "url": "https://example.com" } ``` # Actor output Schema ## `results` (type: `string`): Default dataset items. Each item contains the target URL, detected frameworks, analytics, CDN, hosting, CMS, and server info. ## `summary` (type: `string`): The same single-run summary stored as the OUTPUT key-value record. # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "url": "https://example.com" }; // Run the Actor and wait for it to finish const run = await client.actor("artifact-machine/artifact-machine-tech-stack-analyzer").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${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 = { "url": "https://example.com" } # Run the Actor and wait for it to finish run = client.actor("artifact-machine/artifact-machine-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 '{ "url": "https://example.com" }' | apify call artifact-machine/artifact-machine-tech-stack-analyzer --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=artifact-machine/artifact-machine-tech-stack-analyzer", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Tech Stack Analyzer - Detect Website Technologies", "description": "Detect frameworks, analytics, CDN, hosting, and CMS from any website. HTTP-only, no browser.", "version": "0.1", "x-build-id": "50b8bE638aGWEDVLz" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/artifact-machine~artifact-machine-tech-stack-analyzer/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-artifact-machine-artifact-machine-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/artifact-machine~artifact-machine-tech-stack-analyzer/runs": { "post": { "operationId": "runs-sync-artifact-machine-artifact-machine-tech-stack-analyzer", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/artifact-machine~artifact-machine-tech-stack-analyzer/run-sync": { "post": { "operationId": "run-sync-artifact-machine-artifact-machine-tech-stack-analyzer", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "url" ], "properties": { "url": { "title": "Website URL", "type": "string", "description": "The URL to analyze. If no scheme is provided, https:// is assumed." } } }, "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 } } } } } } } } } } ```