JSON-LD Structured Data Extractor 🧩

Extract the schema.org structured data that any website already publishes for Google — Product, Article, Recipe, Event and more — as clean JSON. No API key. Datacenter-proxy friendly.

Modern sites embed machine-readable structured data (<script type="application/ld+json"> and HTML microdata) so search engines can build rich results. This Actor reads exactly that publicly-published markup and hands it back to you as one dataset item per schema.org entity — flattening @graph blocks, handling arrays, and skipping malformed JSON automatically.

Perfect for SEO audits, rich-result debugging, product/recipe extraction, and feeding clean entities into RAG / LLM pipelines.

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✨ What it does

• Fetches each URL with a real Chrome TLS fingerprint (curl_cffi chrome124) and a plain urllib fallback.
• Parses every application/ld+json block on the page — json.loads each, handling arrays and @graph.
• Flattens @graph into individual entities (a single WordPress/Yoast block often expands to Article + WebPage + BreadcrumbList + Organization + Recipe).
• Optional microdata extraction (itemscope / itemprop) — used automatically as a fallback when a page has no JSON-LD.
• Returns each entity tagged with its source URL, its @type, and a best-effort name.

📥 Input

Field	Type	Default	Description
mode	select	extract	Operation mode (only extract today).
urls	array	—	Page URLs to extract from. https:// is added if missing.
includeMicrodata	boolean	false	Also extract legacy HTML microdata. Off = microdata used only as a fallback.
maxItems	integer	100	Max entities to output across all URLs (max 1000).

{
  "mode": "extract",
  "urls": [
    "https://www.allrecipes.com",
    "https://www.apple.com/iphone-15-pro/"
  ],
  "includeMicrodata": false,
  "maxItems": 100
}

📤 Output

One dataset item per top-level schema.org entity:

{
  "url": "https://www.loveandlemons.com/guacamole-recipe/",
  "schema_type": "Recipe",
  "name": "Best Guacamole Recipe",
  "data": { "@context": "https://schema.org", "@type": "Recipe", "recipeIngredient": ["..."], "...": "full JSON-LD object" },
  "source": "json-ld",
  "scraped_at": "2026-07-23T12:00:00+00:00"
}

• schema_type — the raw @type (string or array, preserved as published).
• name — name / headline / title, whichever is present (nullable).
• data — the full structured-data object, untouched.
• source — json-ld or microdata.

All fields are nullable. Pages with no structured data are skipped with a warning.

💡 Use cases

• SEO structured-data audits — see exactly what Google sees on every page.
• Product / recipe extraction — pull prices, ratings, ingredients, steps straight from the source markup.
• RAG enrichment — clean, typed entities for embeddings and LLM context.
• Rich-result debugging — verify Product, FAQ, Recipe, Event, Breadcrumb markup before it hits Search Console.

💰 Pricing

Pay-per-result, roughly ~$0.50 per 1,000 entities extracted, plus Apify platform usage. Datacenter proxies are fine — no residential proxy or login required.

🔗 Related actors by ninhothedev

• OpenGraph & Metadata Extractor
• SEO On-Page Auditor
• Smart Article Extractor
• Shopify Store Scraper

🏷️ Keywords

json-ld, structured data, schema.org, microdata, rich results, seo audit, product schema, recipe schema, article schema, event schema, rich snippets, google rich results, rag, metadata extractor, web scraping

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This tool only reads data that websites publish publicly for search engines. Respect each site's Terms of Service and robots.txt.