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AgentBIT Structured Metadata Extractor
x402
AgentBIT Structured Metadata Extractor is a paid API for AI agents from agentbit.app, paid per call via x402, $0.01/call, status unknown (last checked 2026-09-13).
Extracts all machine-readable metadata from a webpage (JSON-LD/schema.org, OpenGraph, Twitter Cards, canonical URL, H1, meta description, hreflang, RSS/Atom feeds) into clean structured JSON in a single call.
Price / call$0.01
Success—
StatusUnknown
How this service works
Extract a page's machine-readable self-description in one call: every JSON-LD block (schema.org), OpenGraph and Twitter Card metadata, canonical URL, title, meta description, H1, hreflang alternates and RSS/Atom feed links — parsed server-side into clean JSON. Where text extraction gives you prose, this gives you structured facts.
Output
Returns a JSON object containing: the page's H1, title, meta description, canonical URL, an array of parsed JSON-LD blocks with their schema.org types, OpenGraph tag key-value pairs, Twitter Card tags, hreflang alternate links, RSS/Atom feed URLs, and counts of how many OG tags, Twitter tags, and JSON-LD blocks were found.
Example use cases
SEO audit of a product page
“Grab all the machine-readable metadata from https://example.com/products/blue-widget — I need to see what JSON-LD schema types they're using, the OpenGraph tags, and the canonical URL so I can compare it against our own product pages.”
Content aggregator feed discovery
“Check https://techcrunch.com for any RSS or Atom feed links and grab the page title and meta description while you're at it — I want to start pulling their articles into our pipeline.”
Structured data verification for a blog post
“Fetch the structured metadata from https://agentbit.app/blog — tell me what schema.org types are declared in the JSON-LD, whether there are any hreflang alternates, and what the H1 and canonical URL are.”
Technical details
Endpoint
POSThttps://agentbit.app/v1/web/structuredWhen to prefer
Prefer this endpoint when you need machine-readable structured facts from a page rather than prose text — specifically when you want JSON-LD/schema.org entities, OpenGraph metadata, canonical URLs, hreflang data, or feed discovery in a single parsed call. Use this over a general-purpose text scraper when the goal is semantic metadata (structured data validation, SEO audits, content aggregation setup, or knowledge graph enrichment) rather than reading body copy.
Side effects
- Invalid or non-absolute URL returns a validation error
- Page behind authentication/login wall returns incomplete or empty metadata
- Pages with no structured metadata return null/empty arrays for JSON-LD, hreflang, feeds, etc.
- Timeout if target page is slow to respond
- URL resolves to non-HTML content (PDF, image) — may return minimal or no metadata
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| url | string | Absolute http(s) URL of the page |
Output
Schema · Response
{
"type": "json",
"example": {
"h1": "Engineering Blog",
"url": "https://agentbit.app/blog",
"feeds": null,
"title": "Engineering Blog — AgentBIT",
"counts": {
"og_tags": 2,
"twitter_tags": 0,
"json_ld_blocks": 1
},
"json_ld": [
{
"@type": "TechArticle",
"@context": "https://schema.org",
"headline": "Debugging Bazaar indexing"
}
],
"hreflang": null,
"canonical": "https://agentbit.app/blog",
"open_graph": {
"type": "website",
"title": "Engineering Blog — AgentBIT"
},
"description": "Real-world x402 engineering notes.",
"schema_types": [
"TechArticle"
],
"twitter_card": null
}
}Tags
x402
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