# JSON-LD & Schema.org Structured Data Extractor (`sterlingverify/schema-org-extractor`) Actor

Extract schema.org JSON-LD and Open Graph data from any web page: organisation details (legal name, VAT ID, address, phone, email, social profiles) and products (name, SKU, GTIN, brand, price, currency, availability, rating). Useful for merchant onboarding, catalogue enrichment and price checks.

- **URL**: https://apify.com/sterlingverify/schema-org-extractor.md
- **Developed by:** [Luke Mangan](https://apify.com/sterlingverify) (community)
- **Categories:** SEO tools, Developer tools, Lead generation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$1.00 / 1,000 page extracteds

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/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## Structured Data Extractor

**Structured Data Extractor** pulls schema.org JSON-LD and Open Graph data from any web page: organisation details (legal name, VAT ID, address, phone, email, social profiles) and products (name, SKU, GTIN, brand, price, availability, rating).

**Best for:** Merchant onboarding, product catalogue enrichment, price checks and SEO audits of structured data markup.

### How to extract JSON-LD and schema.org data

1. Add page URLs to **Page URLs** (`startUrls`).
2. Turn on **Include raw JSON-LD** if you want the original blocks too.
3. Click **Start** and download organisation and product data per page.

### How it works

Fetches each page with one normal HTTP GET (no JavaScript rendering, no crawling) and parses `application/ld+json` blocks (including @graph), Product and ProductGroup objects and Open Graph meta tags. Structured data is published by sites specifically for machines to read. Unreachable pages or bad URLs return `ok: false` and are not charged.

### Output

`url, pageTitle, schemaTypes, organization, productCount, products, openGraph, ok`

### Pricing (pay-per-event)

- `page-extracted`: **$0.001** per result ($1 / 1,000). Platform usage is included; you pay only for results.
- Example: 10,000 pages cost $10.00.

### Example input

```json
{
  "startUrls": [
    {
      "url": "https://www.allbirds.co.uk/products/mens-tree-runners"
    },
    {
      "url": "https://www.apple.com/uk/"
    }
  ]
}
```

### Example output

Values below are illustrative.

```json
{
  "url": "https://www.apple.com/uk/",
  "pageTitle": "Apple (United Kingdom)",
  "schemaTypes": [
    "Organization",
    "WebSite"
  ],
  "organization": {
    "name": "Apple",
    "url": "https://www.apple.com/"
  },
  "productCount": 0,
  "products": [],
  "openGraph": {
    "title": "Apple (United Kingdom)"
  },
  "ok": true
}
```

### Use it via API, schedules and integrations

Run it in Apify Console, or call it from your own code with the Apify API or the Python and JavaScript clients. Save an input as a task and add a schedule to run it regularly, and send results to Slack, email, webhooks, Zapier, Make or n8n with Apify integrations. AI agents can find and run it through the Apify MCP server.

```python
from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("sterlingverify/schema-org-extractor").call(run_input={"startUrls": [{"url": "https://www.apple.com/uk/"}]})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)
```

### FAQ

#### Does it render JavaScript or crawl sites?

No. It makes one normal HTTP GET per page and parses the markup the site publishes.

#### What if a page has no structured data?

You get the page with empty fields. Unreachable pages or bad URLs return `ok: false` and are not charged.

### Disclaimer

Only data the site itself publishes in its markup is returned, so it can be missing or out of date. Respect each site's terms and robots rules and don't use it for high-volume scraping. Not affiliated with schema.org.

### Related sterlingVerify tools

Part of the sterlingVerify UK payments, KYB and data toolkit on Apify Store:

- [Payments Stack Detector](https://apify.com/sterlingverify/payments-stack-detector): find which PSPs, wallets and BNPL a store uses
- [Merchant Website Compliance Checker for Onboarding](https://apify.com/sterlingverify/merchant-compliance-checker): onboarding review of a merchant's website
- [SSL Certificate Expiry Monitor](https://apify.com/sterlingverify/ssl-expiry-monitor): bulk SSL certificate expiry checks and alerts

# Actor input Schema

## `startUrls` (type: `array`):

Home pages (for organisation data) or product pages (for products).

## `includeRaw` (type: `boolean`):

Also return up to 50 raw schema.org objects.

## Actor input object example

```json
{
  "startUrls": [
    {
      "url": "https://www.apple.com/uk/"
    }
  ],
  "includeRaw": false
}
```

# Actor output Schema

## `results` (type: `string`):

All results in the default dataset

# 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 '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "startUrls": [
        {
            "url": "https://www.apple.com/uk/"
        }
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("sterlingverify/schema-org-extractor").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 '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "startUrls": [{ "url": "https://www.apple.com/uk/" }] }

# Run the Actor and wait for it to finish
run = client.actor("sterlingverify/schema-org-extractor").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "startUrls": [
    {
      "url": "https://www.apple.com/uk/"
    }
  ]
}' |
apify call sterlingverify/schema-org-extractor --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,sterlingverify/schema-org-extractor"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/ZcGJmoJzgMRfXXlvG/builds/sCELlyyPRcUrCAbiA/openapi.json