# Structured Web Scraper (`scalloped_scotspine/structured-web-scraper`) Actor Extract articles, products, headings, images and links from any website in clean structured JSON format. Supports multiple URLs per run. - **URL**: https://apify.com/scalloped\_scotspine/structured-web-scraper.md - **Developed by:** [Huy Tran](https://apify.com/scalloped_scotspine) (community) - **Categories:** AI, Other, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 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 ## Structured Web Scraper **One URL in, clean data out.** Extract articles, products, headings, images and links from any website — ready to use, no configuration needed. ### What it extracts | Field | Description | |---|---| | `title` | Page title | | `description` | Meta description (up to 300 chars) | | `articles` | Article/post titles, links, scores | | `products` | Product names, prices, links | | `headings` | All H1–H6 headings | | `images` | Image URLs with alt text | | `links` | All outbound links | | `text` | Clean body text (up to 3000 chars) | ### Input ```json { "urls": ["https://news.ycombinator.com/"], "contentType": "all", "extractImages": true, "extractLinks": false, "maxItems": 30 } ```` | Field | Options | Default | |---|---|---| | `urls` | Array of URLs | — | | `contentType` | `all`, `article`, `product` | `all` | | `extractImages` | `true`, `false` | `true` | | `extractLinks` | `true`, `false` | `false` | | `maxItems` | Integer | `30` | ### Supported sites - **Hacker News** — extracts story titles, links, and vote scores - **Generic sites** — auto-detects articles/products by HTML structure - **Fallback** — parses numbered lists from raw text when HTML structure isn't detected ### Output Results are saved to Apify Dataset as structured JSON. Each page produces one record. ### Use cases - Build datasets for LLM training - Monitor news, job boards, product listings - Aggregate content from multiple sources - Power AI agents with fresh web data # Actor input Schema ## `urls` (type: `array`): List of URLs to scrape. Supports any website. ## `contentType` (type: `string`): Type of content to prioritize during extraction. ## `extractImages` (type: `boolean`): Include image URLs and alt text in the output. ## `extractLinks` (type: `boolean`): Include all outbound links found on the page. ## `maxItems` (type: `integer`): Maximum number of items to extract per page before filtering. ## `useAiFilter` (type: `boolean`): Enable AI-powered content filtering. Each article is validated before inclusion. ## `aiProvider` (type: `string`): Which LLM to use for filtering. ## `openaiApiKey` (type: `string`): Your OpenAI API key. Get one at platform.openai.com ## `ollamaUrl` (type: `string`): URL of your Ollama server (e.g. http://your-server:11434). Must be reachable from Apify cloud. ## `aiModel` (type: `string`): Model to use. OpenAI: gpt-4o-mini, gpt-4o. Ollama: llama3, mistral, etc. ## `filterGoal` (type: `string`): Instruction to the AI for what to keep. E.g. 'only tech/programming articles', 'no political content', 'prioritize in-depth technical posts'. ## Actor input object example ```json { "urls": [ "https://news.ycombinator.com/" ], "contentType": "article", "extractImages": true, "extractLinks": false, "maxItems": 30, "useAiFilter": false, "aiProvider": "openai", "ollamaUrl": "http://localhost:11434", "aiModel": "gpt-4o-mini", "filterGoal": "Only keep high-quality, substantive articles. Reject clickbait, ads, and low-effort content." } ``` # Actor output Schema ## `results` (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://news.ycombinator.com/" ], "maxItems": 30, "openaiApiKey": "" }; // Run the Actor and wait for it to finish const run = await client.actor("scalloped_scotspine/structured-web-scraper").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://news.ycombinator.com/"], "maxItems": 30, "openaiApiKey": "", } # Run the Actor and wait for it to finish run = client.actor("scalloped_scotspine/structured-web-scraper").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://news.ycombinator.com/" ], "maxItems": 30, "openaiApiKey": "" }' | apify call scalloped_scotspine/structured-web-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scalloped_scotspine/structured-web-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Structured Web Scraper", "description": "Extract articles, products, headings, images and links from any website in clean structured JSON format. Supports multiple URLs per run.", "version": "0.1", "x-build-id": "gGmInHyc3oyNGoAEr" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scalloped_scotspine~structured-web-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scalloped_scotspine-structured-web-scraper", "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/scalloped_scotspine~structured-web-scraper/runs": { "post": { "operationId": "runs-sync-scalloped_scotspine-structured-web-scraper", "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/scalloped_scotspine~structured-web-scraper/run-sync": { "post": { "operationId": "run-sync-scalloped_scotspine-structured-web-scraper", "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": "URLs to scrape", "type": "array", "description": "List of URLs to scrape. Supports any website.", "items": { "type": "string" } }, "contentType": { "title": "Content type to extract", "enum": [ "article", "product", "search-results", "all" ], "type": "string", "description": "Type of content to prioritize during extraction.", "default": "article" }, "extractImages": { "title": "Extract images", "type": "boolean", "description": "Include image URLs and alt text in the output.", "default": true }, "extractLinks": { "title": "Extract outbound links", "type": "boolean", "description": "Include all outbound links found on the page.", "default": false }, "maxItems": { "title": "Max items per page", "type": "integer", "description": "Maximum number of items to extract per page before filtering.", "default": 30 }, "useAiFilter": { "title": "Use AI filter", "type": "boolean", "description": "Enable AI-powered content filtering. Each article is validated before inclusion.", "default": false }, "aiProvider": { "title": "AI provider", "enum": [ "openai", "ollama" ], "type": "string", "description": "Which LLM to use for filtering.", "default": "openai" }, "openaiApiKey": { "title": "OpenAI API key", "type": "string", "description": "Your OpenAI API key. Get one at platform.openai.com" }, "ollamaUrl": { "title": "Ollama server URL", "type": "string", "description": "URL of your Ollama server (e.g. http://your-server:11434). Must be reachable from Apify cloud.", "default": "http://localhost:11434" }, "aiModel": { "title": "AI model", "type": "string", "description": "Model to use. OpenAI: gpt-4o-mini, gpt-4o. Ollama: llama3, mistral, etc.", "default": "gpt-4o-mini" }, "filterGoal": { "title": "Filter goal", "type": "string", "description": "Instruction to the AI for what to keep. E.g. 'only tech/programming articles', 'no political content', 'prioritize in-depth technical posts'.", "default": "Only keep high-quality, substantive articles. Reject clickbait, ads, and low-effort content." } } }, "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 } } } } } } } } } } ```