# Schema Markup Scraper & SEO Auditor (`autofacts/metadata-scraper`) Actor

Extract JSON-LD, Microdata, RDFa, Open Graph & Twitter Cards. Runs a 0-100 SEO audit — checks canonical, hreflang, headings, image alt, EEAT author signals. Detects 80+ schema.org types including LocalBusiness with NAP, geo coordinates, and Google Place IDs.

- **URL**: https://apify.com/autofacts/metadata-scraper.md
- **Developed by:** [Proooxy](https://apify.com/autofacts) (community)
- **Categories:** Developer tools, Automation, SEO tools
- **Features:** Limited permissions
- **Stats:** 227 total users, 25 monthly users, 100.0% runs succeeded, 8 bookmarks
- **User rating**: 5.00 out of 5 stars

## Pricing

from $3.00 / 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/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

## Schema Markup Scraper & SEO Auditor

Extract structured data, metadata, and SEO signals from any web page. Built for technical SEO auditing, local business intelligence, content aggregation, and competitive analysis.

### 🤖 Use with AI agents

This Actor is built to be called by software. One URL list in, one record per page out, and a
single status field that says whether the run did what you asked.

**MCP** — expose it as a tool to any MCP-capable agent:

```
https://mcp.apify.com?tools=autofacts/metadata-scraper
```

**Minimal request** — everything except `startUrls` has a working default:

```bash
curl -X POST "https://api.apify.com/v2/acts/autofacts~metadata-scraper/run-sync?token=$APIFY_TOKEN" \
  -H 'Content-Type: application/json' \
  -d '{ "startUrls": [{ "url": "https://example.com/product/123" }] }'
```

Use `run-sync` rather than `run-sync-get-dataset-items`: the response carries both
`data.defaultDatasetId` and `data.defaultKeyValueStoreId`, and you need the second one to read
the `SUMMARY` record below. `run-sync-get-dataset-items` returns the rows alone, which leaves
an agent unable to tell an empty result from a failed one.

#### What the user wants → what to send

| The user asks for | Send | Read from each record |
|---|---|---|
| "what schema markup does this page have?" | `{ startUrls }` | `schemaTypes`, `linkedData`, `microdata` |
| "audit this page for SEO" | `{ startUrls }` | `seoAudit.score`, `seoAudit.issues` |
| "check the hreflang setup on these pages" | `{ startUrls, extractGeoData: false, computeSeoScore: false }` | `hreflang.tags`, `hreflang.hasXDefault`, `hreflang.issues` |
| "get the business name, address and phone" | `{ startUrls, extractSeoAnalysis: false }` | `nap`, `localBusiness`, `mapReferences` |
| "who wrote this and when?" | `{ startUrls }` | `authorInfo`, `articleMetadata` |
| "how will this look when shared?" | `{ startUrls, extractSeoAnalysis: false, extractGeoData: false, computeSeoScore: false }` | `openGraph`, `twitterCard`, `icon` |
| "audit a whole section of a site" | `{ startUrls, followLinks: true, maxDepth: 2, maxRequestsPerCrawl: 200 }` | all of the above, one record per page |
| "does this page use RDFa / microformats?" | `{ startUrls, extractRdfa: true, extractHCard: true }` | `rdfa`, `hCards` |

#### Run summary — `SUMMARY`

Every run writes a `SUMMARY` record to its default key-value store, on the success and the
failure path alike:

```
GET https://api.apify.com/v2/key-value-stores/{defaultKeyValueStoreId}/records/SUMMARY
```

```json
{
  "status": "PARTIAL_RESULTS",
  "note": "Some pages were scraped and some URLs failed. …",
  "startUrlCount": 3,
  "pagesScraped": 2,
  "failedUrlCount": 1,
  "failures": [
    { "url": "https://unreachable.example/", "reason": "getaddrinfo ENOTFOUND unreachable.example" }
  ],
  "startedAt": "2026-09-16T03:07:11.402Z",
  "finishedAt": "2026-09-16T03:07:22.596Z"
}
```

| `status` | Meaning | What an agent should do |
|---|---|---|
| `SUCCESS` | Every page fetched produced a record | Use the dataset |
| `PARTIAL_RESULTS` | Some pages scraped, some URLs failed | Use the dataset; report or retry `failures` |
| `NO_RESULTS` | URLs were given, none could be fetched | Retry, or check `failures` for blocks and typos |
| `NO_INPUT` | No start URLs were supplied | Do not retry the same input |
| `RUN_FAILED` | The crawl itself errored | Anything already in the dataset is still valid |

Two details worth knowing before you compare counts:

- **`pagesScraped` below `startUrlCount` with `failedUrlCount: 0` means the crawl hit
  `maxRequestsPerCrawl`.** The status is still `SUCCESS` — nothing failed, the budget simply ran
  out. Raise `maxRequestsPerCrawl` to get the rest.
- **`failures` lists at most 100 entries; `failedUrlCount` is always exact.** On a large run,
  treat the list as a diagnostic sample rather than a complete set.

#### Rules for agents

- **`startUrls` is the whole contract.** This Actor never discovers URLs on its own; it fetches
  what you give it, plus links it finds only when `followLinks` is `true`.
- **One record per page fetched.** A record whose `linkedData` and `microdata` are empty is a
  *valid, successful* result — it means the page declares no structured data. Do not retry it.
- **An empty dataset is not a success here.** Because every reachable page yields exactly one
  record, zero records means nothing was fetched. Check `SUMMARY.status`, not the row count.
- **A failed URL is never in the dataset.** It is in `SUMMARY.failures`, with the reason.
- **Do not invent field names.** The complete field list is in *Output fields* below and in the
  Actor's dataset schema; fields absent from a record were switched off or not declared by the page.
- **Turning extractors off does not reduce cost.** Billing is one event per dataset item, and a
  page produces one item regardless of how many extractors ran. Use the toggles for a smaller,
  cleaner payload, not for a cheaper run.
- **No JavaScript is executed.** A URL whose content is rendered client-side returns the shell of
  the page, which is a correct result for this Actor and a useless one for the user.

### 📖 What it does

This scraper visits one or more URLs and extracts everything a search engine sees: structured data (JSON-LD, Microdata, RDFa), social meta tags (Open Graph, Twitter Cards), and dozens of SEO signals. It then runs an automated audit and returns a 0-100 SEO score with actionable issues — aligned with Google's 2025 ranking signals and EEAT guidelines.

### 🎯 Key capabilities

#### Structured data extraction

- **JSON-LD** — Parses all `<script type="application/ld+json">` blocks, including nested `@graph` structures
- **Microdata** — Extracts `itemscope`/`itemprop` schema.org markup with full nesting support
- **RDFa** *(opt-in)* — Parses `typeof`/`property`/`vocab` attributes with schema.org vocabulary resolution
- **Schema type detection** — Identifies all schema.org types present (Product, Article, LocalBusiness, BreadcrumbList, etc.)

#### Social & meta tags

- **Open Graph** — All `og:*` properties (title, description, image, type, locale, etc.)
- **Twitter Cards** — All `twitter:*` properties with special handling for `summary_large_image`
- **Dublin Core** — `DC.*` and `DCTerms.*` academic/institutional metadata
- **Standard meta tags** — viewport, description, keywords, robots, theme-color, and all others

#### SEO analysis

- **Canonical URL** — Detects `<link rel="canonical">`
- **Robots meta** — Extracts directives for `robots`, `googlebot`, `bingbot`, etc.
- **Heading hierarchy** — Maps H1–H6 structure, counts H1 tags, detects skipped levels
- **Image alt text audit** — Counts images with/without alt attributes, calculates coverage percentage
- **Viewport & charset** — Verifies mobile-first indexing prerequisites
- **SEO score (0-100)** — Automated audit checking 15 Google ranking signals with error/warning/info severity

#### International SEO

- **Hreflang tags** — Extracts all `<link rel="alternate" hreflang="...">` with built-in validation:
  - Flags missing `x-default` fallback
  - Validates ISO 639-1 language codes (catches common mistakes like `en-UK` → should be `en-GB`)
  - Detects missing self-referencing tags
- **Language detection** — `<html lang>`, `<meta http-equiv="content-language">`, `og:locale`

#### EEAT & author signals

- **Author extraction** — Pulls author info from JSON-LD (`Person` type with `sameAs` links), `<meta name="author">`, and `<a rel="author">`
- **Article metadata** — `datePublished`, `dateModified`, `headline`, `wordCount`, `publisher` from Article/NewsArticle/BlogPosting schema

#### Local / Geo SEO

- **LocalBusiness extraction** — Detects 80+ schema.org LocalBusiness subtypes (Restaurant, Hotel, Dentist, Store, etc.) and extracts NAP, geo coordinates, opening hours, price range
- **NAP (Name/Address/Phone)** — From any Organization or LocalBusiness schema
- **Geo meta tags** — `geo.region`, `geo.placename`, `geo.position`, `ICBM`
- **Google Maps references** — Embedded map iframes, Place IDs, CID numbers
- **hCard/vCard** *(opt-in)* — `.vcard`/`.h-card` microformat contact data

#### Breadcrumb validation

- Extracts `BreadcrumbList` schema items with position, name, and URL
- Validates sequential positions and flags relative URLs

### 📋 Input parameters

| Parameter | Type | Default | Description |
|-----------|------|---------|-------------|
| `startUrls` | Array | *(required)* | URLs to scrape |
| `proxy` | Object | Apify Proxy | Proxy configuration |
| `maxRequestsPerCrawl` | Integer | `100` | Maximum pages to scrape (1–100,000) |
| `maxConcurrency` | Integer | `10` | Parallel pages (1–100) |
| `followLinks` | Boolean | `false` | Also crawl links found on the start pages |
| `maxDepth` | Integer | `0` | Link hops to follow past a start URL (needs `followLinks`) |
| `extractMetaTags` | Boolean | `true` | Extract all meta tags |
| `extractSeoAnalysis` | Boolean | `true` | SEO signals: canonical, hreflang, robots, headings, author, images, breadcrumbs, Dublin Core, viewport, charset |
| `extractGeoData` | Boolean | `true` | Geo tags, LocalBusiness, NAP, Google Maps references |
| `computeSeoScore` | Boolean | `true` | Run SEO audit (0-100 score + issues list) |
| `extractRdfa` | Boolean | `false` | RDFa structured data (opt-in) |
| `extractHCard` | Boolean | `false` | hCard/vCard microformats (opt-in) |

### 🗂️ Output fields

Each scraped page produces a JSON object with these fields:

#### Core metadata

| Field | Type | Description |
|-------|------|-------------|
| `url` | String | Final URL after redirects |
| `title` | String | Page `<title>` content |
| `icon` | String | Favicon/apple-touch-icon URL |
| `linkedData` | Array | JSON-LD structured data blocks |
| `microdata` | Array | Microdata (schema.org) items |
| `openGraph` | Object | Open Graph properties |
| `twitterCard` | Object | Twitter Card properties |
| `metaTags` | Object | All other meta tags |

#### SEO analysis (when `extractSeoAnalysis` is enabled)

| Field | Type | Description |
|-------|------|-------------|
| `canonical` | String/null | Canonical URL |
| `robotsMeta` | Object | Robots directives (`{ robots: "index, follow", googlebot: "noarchive" }`) |
| `hreflang` | Object | `{ tags: [{lang, url}], hasXDefault: bool, issues: string[] }` |
| `language` | Object | `{ htmlLang, contentLanguage, ogLocale }` |
| `dublinCore` | Object | Dublin Core metadata |
| `viewport` | String/null | Viewport meta tag content |
| `charset` | String/null | Character encoding |
| `headings` | Object | `{ headings: [{level, text}], h1Count, issues[] }` |
| `imageAudit` | Object | `{ totalImages, imagesWithAlt, imagesWithoutAlt, altTexts[], issues[] }` |
| `authorInfo` | Object/null | `{ name, url, sameAs[], jobTitle, source }` |
| `schemaTypes` | Array | All schema.org types detected (e.g., `["Product", "BreadcrumbList"]`) |
| `articleMetadata` | Object/null | `{ datePublished, dateModified, headline, description, wordCount, publisher }` |
| `breadcrumbs` | Object/null | `{ items: [{position, name, url}], issues[] }` |

#### Geo / Local SEO (when `extractGeoData` is enabled)

| Field | Type | Description |
|-------|------|-------------|
| `geoTags` | Object/null | Geo meta tags (`{ region, placename, position, icbm }`) |
| `localBusiness` | Object/null | LocalBusiness schema data with NAP, geo coordinates, opening hours |
| `nap` | Object/null | Name, Address, Phone from Organization/LocalBusiness |
| `mapReferences` | Object/null | `{ googleMapsEmbeds[], placeIds[], cids[] }` |

#### SEO audit (when `computeSeoScore` is enabled)

| Field | Type | Description |
|-------|------|-------------|
| `seoAudit` | Object | `{ score: 0-100, issues: [{severity, code, message}] }` |

#### Optional extractors

| Field | Type | Description |
|-------|------|-------------|
| `rdfa` | Array | RDFa structured data (when `extractRdfa` is enabled) |
| `hCards` | Array | hCard/vCard contact data (when `extractHCard` is enabled) |

### ✅ SEO audit checks

The audit starts at 100 and deducts points for each issue found:

| Check | Severity | Points | What it catches |
|-------|----------|--------|-----------------|
| Missing `<title>` | Error | -10 | Core ranking signal |
| Title > 60 chars | Warning | -5 | SERP truncation |
| Missing meta description | Error | -10 | CTR impact |
| Description > 160 chars | Warning | -5 | SERP truncation |
| Missing or multiple H1 | Error | -10 | Content hierarchy |
| Missing canonical URL | Warning | -5 | Duplicate content risk |
| Missing og:title | Warning | -5 | Social share CTR |
| Missing og:description | Warning | -5 | Social share CTR |
| Missing og:image | Warning | -5 | Social CTR (40-60% impact) |
| No structured data | Warning | -5 | Rich results eligibility |
| Missing favicon | Warning | -5 | Brand trust signal |
| Missing viewport | Warning | -5 | Mobile-first indexing |
| Missing hreflang x-default | Warning | -5 | International SEO trust |
| Missing author (on articles) | Warning | -5 | EEAT signal |
| Missing datePublished (on articles) | Warning | -5 | Freshness signal |
| > 50% images without alt | Warning | -5 | Accessibility + AI |
| No BreadcrumbList (deep pages) | Info | -1 | Navigation hierarchy |

### 💡 Use cases

#### Technical SEO audit

Crawl your site and get an instant SEO health check across every page. Identify missing titles, broken heading hierarchies, absent structured data, and more — with a prioritized issues list.

#### E-commerce competitive analysis

Extract product schema (pricing, availability, reviews, return policies), breadcrumb structures, and rich snippet eligibility from competitor product pages.

#### Local business intelligence

Scrape LocalBusiness schema from directories, review sites, or business websites. Extract NAP data, opening hours, geo coordinates, Google Place IDs, and CID numbers for lead generation or data enrichment.

#### International SEO validation

Audit hreflang implementations across multilingual sites. Catch the errors that 75% of implementations contain: missing x-default fallbacks, invalid ISO codes, missing self-references.

#### EEAT & content analysis

Extract author information, `sameAs` links to verified profiles, publication dates, and publisher data from article pages. Monitor how well your content signals expertise and authority.

#### Social media preview testing

Verify how pages will appear when shared on Facebook (Open Graph) and Twitter/X (Twitter Cards). Check for missing images, truncated descriptions, and incomplete metadata.

#### Content aggregation

Build news aggregators or content feeds by extracting article metadata, publication dates, authors, and descriptions from multiple sources in a single crawl.

### 📤 Example output

#### News article (CNN)

```json
{
  "url": "https://edition.cnn.com/2025/04/18/politics/...",
  "title": "Supreme Court temporarily pauses deportations under Alien Enemies Act",
  "canonical": "https://www.cnn.com/2025/04/18/politics/...",
  "language": {
    "htmlLang": "en",
    "contentLanguage": null,
    "ogLocale": "en_US"
  },
  "hreflang": {
    "tags": [
      { "lang": "en-gb", "url": "https://edition.cnn.com/..." },
      { "lang": "en-us", "url": "https://www.cnn.com/..." },
      { "lang": "x-default", "url": "https://edition.cnn.com/..." }
    ],
    "hasXDefault": true,
    "issues": ["Missing self-referencing hreflang tag"]
  },
  "authorInfo": {
    "name": "Tierney Sneed, John Fritze",
    "url": null,
    "sameAs": [],
    "jobTitle": null,
    "source": "meta"
  },
  "schemaTypes": ["NewsArticle", "Person", "ImageObject", "Organization", "WebPage", "NewsMediaOrganization"],
  "seoAudit": {
    "score": 79,
    "issues": [
      { "severity": "warning", "code": "TITLE_TOO_LONG", "message": "Title is 94 chars (recommended: max 60)" },
      { "severity": "warning", "code": "DESCRIPTION_TOO_LONG", "message": "Meta description is 267 chars (recommended: max 160)" },
      { "severity": "warning", "code": "MISSING_DATE_PUBLISHED", "message": "Article page missing datePublished (impacts freshness signals)" },
      { "severity": "info", "code": "NO_BREADCRUMBS", "message": "Deep page with no BreadcrumbList schema (helps navigation hierarchy)" }
    ]
  }
}
```

#### E-commerce product (Farfetch)

```json
{
  "url": "https://www.farfetch.com/shopping/women/jacquemus-les-doubles-sandals-item-28543291.aspx",
  "title": "Jacquemus Les Doubles Sandals | Brown | FARFETCH",
  "canonical": "https://www.farfetch.com/shopping/women/jacquemus-les-doubles-sandals-item-28543291.aspx",
  "schemaTypes": ["ProductGroup", "ImageObject", "Brand", "Product", "Offer", "MerchantReturnPolicy", "UnitPriceSpecification", "BreadcrumbList", "ListItem"],
  "breadcrumbs": {
    "items": [
      { "position": 1, "name": "Women Home", "url": "/shopping/women/items.aspx" },
      { "position": 2, "name": "Jacquemus", "url": "/shopping/women/jacquemus/items.aspx" },
      { "position": 3, "name": "Shoes", "url": "/shopping/women/jacquemus/shoes-1/items.aspx" },
      { "position": 4, "name": "Heeled Sandals", "url": "/shopping/women/jacquemus/heeled-sandals-1/items.aspx" }
    ],
    "issues": ["Relative URL in breadcrumb position 1: \"/shopping/women/items.aspx\""]
  },
  "headings": {
    "h1Count": 1,
    "issues": ["Skipped heading level: h2 to h4"]
  },
  "imageAudit": {
    "totalImages": 6,
    "imagesWithAlt": 5,
    "imagesWithoutAlt": 1,
    "issues": ["1 image(s) missing alt attribute"]
  },
  "robotsMeta": { "robots": "noindex" },
  "seoAudit": { "score": 100, "issues": [] }
}
```

#### Wikipedia (RDFa + hCard)

```json
{
  "url": "https://en.wikipedia.org/wiki/San_Francisco",
  "title": "San Francisco - Wikipedia",
  "canonical": "https://en.wikipedia.org/wiki/San_Francisco",
  "schemaTypes": ["Article", "Organization", "ImageObject"],
  "authorInfo": {
    "name": "Contributors to Wikimedia projects",
    "source": "json-ld"
  },
  "articleMetadata": {
    "datePublished": "2001-11-13T04:30:40Z",
    "dateModified": "2026-03-28T17:14:57Z",
    "headline": "consolidated city and county in California, United States",
    "publisher": { "name": "Wikimedia Foundation, Inc." }
  },
  "rdfa": ["... 114 RDFa items extracted ..."],
  "hCards": [{ "name": "San Francisco", "... ": "..." }],
  "imageAudit": {
    "totalImages": 119,
    "imagesWithAlt": 43,
    "imagesWithoutAlt": 76,
    "issues": ["64% of images missing alt text (accessibility + AI understanding)"]
  },
  "seoAudit": {
    "score": 80,
    "issues": [
      { "severity": "error", "code": "MISSING_DESCRIPTION", "message": "Page has no meta description" },
      { "severity": "warning", "code": "MISSING_OG_DESCRIPTION", "message": "Missing og:description meta tag" },
      { "severity": "warning", "code": "IMAGES_MISSING_ALT", "message": "64% of images missing alt text" }
    ]
  }
}
```

### 🛠️ Technical details

- **Engine**: CheerioCrawler (server-side HTML parsing, no JavaScript execution)
- **Runtime**: Node.js 22, Apify SDK 3.5.3, Crawlee 3.15.3
- **Performance**: Lightweight and fast — no browser overhead
- **Sessions**: Automatic session rotation with cookie persistence
- **Proxies**: Full proxy support including Apify Proxy residential groups
- **Retries**: Up to 3 retries per request with automatic session rotation on blocks
- **Link following**: Optional crawling with configurable depth

### 💳 Pricing

This Actor uses **pay per event** — you are charged per URL audited and saved to the dataset, not for compute time.

| Event | Free / Starter | Scale / Business+ |
| :--- | ---: | ---: |
| URL audited and saved | $0.0050 | $0.0030 |

**What the free plan gets you:** Apify's free plan includes $5 of platform credit every month, which is about **1,000 URLs audited per month at no cost**. A 10,000-page site audit costs $50 on the free/starter rate, $30 on Scale or above.

There is no per-run start fee. You are never charged for URLs that fail to load. Set **Max total charge** on the run to cap spend on large crawls.

***

### ⚠️ Limitations

- **No JavaScript rendering** — Pages that require JS to load content (e.g., SPAs, IMDB) will return minimal data. Use a browser-based scraper for these.
- **Anti-bot protection** — Some sites (Yelp, BBC, Medium) may block requests even with residential proxies. Results depend on proxy quality.
- **RDFa complexity** — The RDFa extractor handles the common schema.org vocabulary case. Exotic namespace prefixes may not be fully resolved.
- **No performance scoring** — Page speed, Core Web Vitals and Lighthouse categories are deliberately out of scope. Measuring them needs a real browser; this Actor is HTTP-only by design, which is what makes it fast and cheap. Pair it with a dedicated performance Actor if you need both.

***

### 🧰 Other Actors by autofacts

Apify only auto-recommends Actors in the same category, so here are the ones that actually pair with this scraper:

| Actor | What it's for |
| :--- | :--- |
| [HTML to PDF & URL to PDF API](https://apify.com/autofacts/universal-web-printer) | Render the audited page to PDF/PNG for the report |
| [Google Ads Scraper](https://apify.com/autofacts/google-ads-scraper) | Every Google ad a competitor runs, with the landing pages to audit here |
| [Google Trends API & Scraper](https://apify.com/autofacts/google-trends) | The searches rising around a topic, and where, before you write the page to audit here |
| [Google Trends Trending Now](https://apify.com/autofacts/google-trends-trending-now) | What people search for right now, in each of 125 countries |
| [YouTube Transcript Scraper API](https://apify.com/autofacts/youtube-subtitle-transcript-scraper) | Pull video captions as clean text for content and RAG pipelines |
| [Shopify Store Leads](https://apify.com/autofacts/shopify-store-leads) | Find Shopify stores to audit in bulk |
| [Shopify Scraper](https://apify.com/autofacts/shopify) | Full product and collection data once a store is worth a closer look |

All of them: [apify.com/autofacts](https://apify.com/autofacts)

# Actor input Schema

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

URLs to start crawling from

## `followLinks` (type: `boolean`):

Also crawl links found on the start pages, up to Max Depth. Off by default: without it the Actor fetches exactly the URLs you submit.

## `maxDepth` (type: `integer`):

How many link hops past a start URL to follow. Only applies when Follow Links is on. 0 means the start URLs only.

## `maxRequestsPerCrawl` (type: `integer`):

Maximum number of pages that the scraper will open. The crawl will stop when this limit is reached.

## `maxConcurrency` (type: `integer`):

Maximum number of pages that will be processed in parallel.

## `extractMetaTags` (type: `boolean`):

Extract all meta tags from the page

## `extractSeoAnalysis` (type: `boolean`):

Extract SEO signals: canonical URL, hreflang (with validation), robots meta, heading hierarchy, author/EEAT info, image alt audit, article metadata, breadcrumbs, Dublin Core, viewport, and charset

## `extractGeoData` (type: `boolean`):

Extract geo meta tags, LocalBusiness schema, NAP (Name/Address/Phone), and Google Maps/Place ID references

## `computeSeoScore` (type: `boolean`):

Run an SEO audit producing a 0-100 score and list of issues aligned with Google ranking signals

## `extractRdfa` (type: `boolean`):

Extract RDFa structured data (niche format, opt-in)

## `extractHCard` (type: `boolean`):

Extract hCard/vCard microformat contact data (niche format, opt-in)

## `proxy` (type: `object`):

Select proxies to be used by your crawler.

## Actor input object example

```json
{
  "startUrls": [
    {
      "url": "https://apify.com"
    }
  ],
  "followLinks": false,
  "maxDepth": 0,
  "maxRequestsPerCrawl": 100,
  "maxConcurrency": 10,
  "extractMetaTags": true,
  "extractSeoAnalysis": true,
  "extractGeoData": true,
  "computeSeoScore": true,
  "extractRdfa": false,
  "extractHCard": false,
  "proxy": {
    "useApifyProxy": true
  }
}
```

# Actor output Schema

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

// Prepare Actor input
const input = {
    "startUrls": [
        {
            "url": "https://apify.com"
        }
    ],
    "proxy": {
        "useApifyProxy": true
    }
};

// Run the Actor and wait for it to finish
const run = await client.actor("autofacts/metadata-scraper").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://apify.com" }],
    "proxy": { "useApifyProxy": True },
}

# Run the Actor and wait for it to finish
run = client.actor("autofacts/metadata-scraper").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://apify.com"
    }
  ],
  "proxy": {
    "useApifyProxy": true
  }
}' |
apify call autofacts/metadata-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,autofacts/metadata-scraper"
        }
    }
}
```

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/kFimovrHDxYee5jzc/builds/Rb9UdDT4jejoYefLd/openapi.json