# Metascraper — Web Metadata Extractor (`ntriqpro/metascraper-actor`) Actor Extract structured metadata (title, description, author, image, publisher, date) from any web page using the metascraper library. - **URL**: https://apify.com/ntriqpro/metascraper-actor.md - **Developed by:** [daehwan kim](https://apify.com/ntriqpro) (community) - **Categories:** Developer tools, AI, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $0.50 / 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. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 ### What does Metascraper Actor do? **Metascraper Actor** extracts structured metadata from any web page — title, description, author, publisher, date, image, logo, and language — in a single API call. It is powered by the open-source [metascraper](https://github.com/microlinkhq/metascraper) library (MIT license). Provide a list of URLs and receive clean, structured JSON. No browser required — fast HTTP-based extraction works for most public pages. Results are stored in an Apify Dataset and downloadable in JSON, CSV, Excel, or HTML. ### Why use Metascraper Actor? - **Content research**: harvest article titles, authors, publish dates, and featured images at scale. - **SEO auditing**: check Open Graph / Twitter Card metadata across pages. - **Feed generation**: build structured feeds from arbitrary web pages without RSS. - **Data enrichment**: enrich link lists with titles, descriptions, and thumbnails. - **Scheduling**: run on a schedule via Apify Console to monitor metadata changes. ### How to use Metascraper Actor 1. Open the Actor in [Apify Console](https://console.apify.com). 2. In the **Input** tab, enter one or more URLs under **URLs to scrape**. 3. Optionally set **Max items** to limit processing. 4. Click **Start** and wait a few seconds. 5. View results in the **Output** tab or download from the **Dataset** tab. ### Input | Field | Type | Description | |---|---|---| | `urls` | string[] | List of web page URLs to process (required) | | `maxItems` | integer | Max URLs to process (0 = no limit, default 10) | | `proxyConfiguration` | object | Optional Apify proxy settings | Example input: ```json { "urls": [ "https://www.apify.com/", "https://crawlee.dev/" ], "maxItems": 5 } ```` ### Output Each processed URL produces one JSON record in the dataset. ```json { "url": "https://www.apify.com/", "pageTitle": "Apify: Full-Stack Web Scraping and Data Extraction Platform", "pageDescription": "Extract structured data from any website at scale.", "author": null, "publisher": "Apify", "publishedDate": null, "imageUrl": "https://apify.com/og-image.png", "logoUrl": "https://apify.com/favicon.ico", "lang": "en" } ``` You can download the dataset in various formats such as JSON, HTML, CSV, or Excel. ### Data fields | Field | Description | |---|---| | `url` | Final URL after redirects | | `pageTitle` | Page title | | `pageDescription` | Meta description | | `author` | Content author | | `publisher` | Site publisher / brand name | | `publishedDate` | Publish or modified date | | `imageUrl` | Featured / Open Graph image | | `logoUrl` | Site logo | | `lang` | Page language code | | `error` | Error message if fetch failed (only present on failure) | ### Pricing / Cost estimation This Actor uses the **Pay-per-event** model. Each URL processed counts as one event. Typical cost is fractions of a cent per URL. Apify offers a **free tier** with $5/month of platform credits — enough for thousands of metadata extractions. ### Tips - For pages behind paywalls or heavy JS rendering, consider pairing with a browser-based Actor. - Use `maxItems` during testing to avoid unnecessary costs. - Schedule the Actor via Apify Console to track metadata changes over time. ### FAQ, Disclaimers, and Support **Is it legal?** This Actor fetches publicly accessible web pages using standard HTTP requests, the same way a browser does. It is your responsibility to comply with each website's Terms of Service, robots.txt, and applicable laws (GDPR, CCPA, etc.). The Actor does not bypass authentication or access non-public data. **Known limitations:** Pages requiring JavaScript execution or login are not supported. For JS-heavy sites, the metadata extraction may be incomplete. **Issues or feature requests?** Use the **Issues** tab on the Actor page. *** > **Legal Disclaimer:** This Actor is an unofficial integration of metascraper. Not affiliated with original project. *** ### 🔗 Related Actors by ntriqpro Extend this actor with the ntriqpro intelligence network: - [**video-intelligence-analyzer**](https://apify.com/ntriqpro/video-intelligence-analyzer) — Video/image AI analyzer (transcripts, scenes, objects) - [**vehicle-damage-assessment**](https://apify.com/ntriqpro/vehicle-damage-assessment) — Vehicle damage AI assessment - [**table-chart-extractor**](https://apify.com/ntriqpro/table-chart-extractor) — Table and chart data extraction ### ⭐ Love it? Leave a Review Your rating helps professionals discover this actor. [Rate it here](https://apify.com/ntriqpro/metascraper-actor/reviews). # Actor input Schema ## `urls` (type: `array`): List of web page URLs to extract metadata from. ## `maxItems` (type: `integer`): Maximum number of URLs to process. Set to 0 for no limit. ## `proxyConfiguration` (type: `object`): Optional proxy settings to avoid blocks during scraping. ## Actor input object example ```json { "urls": [ "https://www.apify.com/", "https://crawlee.dev/", "https://github.com/microlinkhq/metascraper" ], "maxItems": 10, "proxyConfiguration": { "useApifyProxy": false } } ``` # 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://www.apify.com/", "https://crawlee.dev/", "https://github.com/microlinkhq/metascraper" ], "maxItems": 10, "proxyConfiguration": { "useApifyProxy": false } }; // Run the Actor and wait for it to finish const run = await client.actor("ntriqpro/metascraper-actor").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://www.apify.com/", "https://crawlee.dev/", "https://github.com/microlinkhq/metascraper", ], "maxItems": 10, "proxyConfiguration": { "useApifyProxy": False }, } # Run the Actor and wait for it to finish run = client.actor("ntriqpro/metascraper-actor").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://www.apify.com/", "https://crawlee.dev/", "https://github.com/microlinkhq/metascraper" ], "maxItems": 10, "proxyConfiguration": { "useApifyProxy": false } }' | apify call ntriqpro/metascraper-actor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=ntriqpro/metascraper-actor", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Metascraper — Web Metadata Extractor", "description": "Extract structured metadata (title, description, author, image, publisher, date) from any web page using the metascraper library.", "version": "1.0", "x-build-id": "k4mY5UyQl1LAlUmUE" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/ntriqpro~metascraper-actor/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-ntriqpro-metascraper-actor", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/ntriqpro~metascraper-actor/runs": { "post": { "operationId": "runs-sync-ntriqpro-metascraper-actor", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/ntriqpro~metascraper-actor/run-sync": { "post": { "operationId": "run-sync-ntriqpro-metascraper-actor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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 web page URLs to extract metadata from.", "items": { "type": "string" } }, "maxItems": { "title": "Max items", "minimum": 0, "type": "integer", "description": "Maximum number of URLs to process. Set to 0 for no limit." }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Optional proxy settings to avoid blocks during scraping." } } }, "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 } } } } } } } } } } ```