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Schema Markup Generator — JSON-LD Structured Data

Generate Google-approved JSON-LD structured data for 30+ Schema.org types. Supports SEO schema like Article, Product, FAQ, Event, LocalBusiness, and more.

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from $0.01 / actor start

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Perry AY

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Schema Markup Generator — JSON-LD Structured Data for SEO

Generate Google-approved JSON-LD structured data for 30+ Schema.org types in one call. Whether you need an Article, Product, FAQ, Event, LocalBusiness, Recipe, or any of 25+ other schema types, this actor produces valid, ready-to-use JSON-LD markup — no manual template writing required.

What does it do?

Schema Markup Generator takes your content data and a schema type, then generates the correct JSON-LD structured data following Schema.org specifications. It understands required vs. recommended fields per schema type, validates your data, and produces clean markup you can drop directly into your HTML <head> or test in Google's Rich Results Test.

Who is it for?

Persona	What they use it for
SEO Professional	Generating structured data for content pages, products, and local business listings
Web Developer	Adding JSON-LD to websites without writing schema templates manually
Content Marketer	Creating rich snippets for blog posts, FAQs, recipes, and events
E-commerce Manager	Generating Product and ProductGroup markup for product catalog pages
Data Analyst	Building Dataset schema for structured data publishing
QA Tester	Validating schema markup across thousands of pages in bulk

Features

30+ schema types — Article, Product, FAQ, Event, LocalBusiness, Recipe, Person, Organization, BreadcrumbList, BlogPosting, Book, Course, CreativeWork, Dataset, EducationalCredential, FactCheck, HowTo, ImageObject, JobPosting, Movie, MusicAlbum, MusicGroup, NewsArticle, PodcastEpisode, ProductGroup, Question, Review, SoftwareApplication, VideoObject, WebPage, WebSite
Bulk generation — Process hundreds of items from a JSON array in a single run
Built-in validation — Checks required fields, recommended fields, and unknown fields per schema type
Flexible output — Raw JSON-LD or complete HTML <script type="application/ld+json"> tags
Context control — Optionally include/exclude @context for embedding in existing JSON-LD blocks
Type-safe serialization — Automatic datetime/date to ISO-8601 conversion, camelCase field mapping

Quick Start

# Single Article
python3 scripts/apify_control.py run-sync-get <ACTOR_ID> '{
  "schemaType": "Article",
  "data": {
    "name": "How to Optimize JSON-LD for SEO",
    "author": "Jane Doe",
    "datePublished": "2026-07-27",
    "description": "A comprehensive guide."
  }
}'

# Product with offers
python3 scripts/apify_control.py run-sync-get <ACTOR_ID> '{
  "schemaType": "Product",
  "data": {
    "name": "Wireless Headphones",
    "description": "Noise-cancelling Bluetooth headphones",
    "brand": "Acme Audio",
    "offers": {
      "@type": "Offer",
      "price": 79.99,
      "priceCurrency": "USD",
      "availability": "https://schema.org/InStock"
    }
  }
}'

# FAQ Page
python3 scripts/apify_control.py run-sync-get <ACTOR_ID> '{
  "schemaType": "FAQ",
  "data": {
    "mainEntity": [
      {"name": "What is JSON-LD?", "text": "JSON-LD is a way to structure data."},
      {"name": "Why use structured data?", "text": "It improves search visibility."}
    ]
  }
}'

# Bulk generation
python3 scripts/apify_control.py run-sync-get <ACTOR_ID> '{
  "schemaType": "Article",
  "items": [
    {"name": "First Article", "author": "Alice", "datePublished": "2026-01-01"},
    {"name": "Second Article", "author": "Bob", "datePublished": "2026-02-01"}
  ]
}'

Output Example

{
  "schemaType": "Article",
  "index": 0,
  "fieldCount": 4,
  "jsonLd": {
    "@context": "https://schema.org",
    "@type": "Article",
    "name": "How to Optimize JSON-LD for SEO",
    "author": "Jane Doe",
    "datePublished": "2026-07-27",
    "description": "A comprehensive guide."
  },
  "valid": true,
  "errors": [],
  "warnings": [
    "Missing recommended field: 'image'",
    "Missing recommended field: 'publisher'"
  ],
  "success": true,
  "scriptTag": null
}

Script Tag Output

When outputFormat is script-tag, each result includes a scriptTag field:

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "Article",
  "name": "Example Article",
  "author": "Jane Doe"
}
</script>

Input Parameters

Field	Type	Required	Description
`schemaType`	string	✅ Yes	Schema.org type (one of 32 supported types)
`data`	object	See note	Single item's structured data fields
`items`	array	See note	Array of data objects for bulk generation
`outputFormat`	string	No	`json-ld` (default) or `script-tag`
`includeContext`	boolean	No	Include `@context` field (default: true)
`validateMarkup`	boolean	No	Run validation (default: true)

Note: Either data or items must be provided. If both are provided, items takes precedence.

Supported Schema Types

Category	Types
Articles	Article, BlogPosting, NewsArticle
Products	Product, ProductGroup
Business	LocalBusiness, Organization
Media	ImageObject, VideoObject, Movie
Music	MusicAlbum, MusicGroup
Events	Event
People	Person
Lists	BreadcrumbList
FAQs	FAQ (FAQPage)
Recipes	Recipe, HowTo
Education	Course, EducationalOccupationalCredential
Reviews	Review, EmployerAggregateRating
Creative	CreativeWork, Book, FactCheck, Question
Data	Dataset
Jobs	JobPosting
Audio	PodcastEpisode
Software	SoftwareApplication
Web	WebPage, WebSite

Input Schema

{
  "schemaType": "Article",
  "data": {
    "name": "Example Article",
    "description": "Article description",
    "url": "https://example.com/article"
  }
}

Why use this?

No manual schema templates — Choose a type, provide your data, get valid JSON-LD
Bulk processing — Generate markup for hundreds of pages in a single run
Validation built in — Catches missing required fields and warns about missing recommended ones
SEO-ready output — Works directly with Google Rich Results, Bing Webmaster Tools, and Yandex
Developer-friendly — Clean JSON output, script tag support, and batched input

FAQ

What schema types are supported? 30+ types including Article, Product, FAQ, Event, LocalBusiness, Recipe, and more. See the Supported Schema Types section for the full list.
Is the output Google Rich Results compatible? Yes. The generated JSON-LD follows Schema.org specifications and passes Google Rich Results Test validation.
Can I use this in CI/CD pipelines? Yes. The API-first design lets you integrate schema generation into build pipelines using the Apify API.
What's the difference between data and items? data is for a single item, items is an array for bulk processing. If both are provided, items takes precedence.
Does this actor validate existing schema markup? It generates new markup and validates its own output against Schema.org requirements. For auditing existing markup, see our Schema Validator tools.
Can I customize the output format? Yes. Choose between raw JSON-LD (json-ld) or complete HTML script tags (script-tag).
What happens if validation fails? The actor returns detailed error messages explaining which fields are missing or invalid.
How many items can I process in bulk? There's no hard limit, but we recommend keeping batches under 100 items for optimal performance.
Do I need an API key for this actor? No external API keys needed. Just an Apify account.
Can I generate multiple schema types in one run? No. Each run handles one schema type. Use multiple runs or the bulk mode with items.

MCP Integration

Add this actor to your MCP client:

{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com"
    }
  }
}

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SEO Keywords

JSON-LD generator, schema markup, structured data, rich results, SEO schema, Schema.org generator, FAQ schema, Product schema, Article schema, JSON-LD validator, semantic SEO, Google rich snippets

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