# JSON-LD Structured Data Extractor (`gifted_wagon/json-ld-schema-evidence-extractor`) Actor

Extract, validate, and flatten JSON-LD schema nodes with block evidence, type inventory, malformed-block reporting, and page metadata context.

- **URL**: https://apify.com/gifted\_wagon/json-ld-schema-evidence-extractor.md
- **Developed by:** [Michael Olmos](https://apify.com/gifted_wagon) (community)
- **Categories:** SEO tools, Developer tools, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $3.50 / 1,000 page analyzeds

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?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
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.
Actors are written with capital "A".

## 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.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## JSON-LD Schema Evidence Extractor

Extract JSON-LD from public HTML pages without hiding the evidence. The Actor preserves each script block, flattens `@graph` nodes, inventories Schema.org types, reports malformed blocks alongside valid blocks, and adds canonical, title, and Open Graph context.

### Safety and scope

- Public HTTP(S) only with private-network DNS and redirect blocking.
- Up to 1,000 unique pages, 30 concurrent requests, 60-second request limits, 5 redirect hops, and 5 MB HTML responses.
- This is structural extraction, not a guarantee that markup is eligible for a search-engine rich result.

### Charging

PAY\_PER\_EVENT uses a one-time Actor-start event plus `page-analyzed`. Only successful HTML page analyses are charged. Fetch failures, blocked targets, invalid inputs, and the OUTPUT summary are not charged. A successfully fetched page with zero or malformed JSON-LD is a completed analysis and is charged because the evidence is the result.

```json
{"urls":["https://apify.com"],"maxPages":1,"includeRaw":true,"timeoutSecs":20,"concurrency":1}
```

# Actor input Schema

## `urls` (type: `array`):

Public HTML pages to analyze for JSON-LD evidence.

## `maxPages` (type: `integer`):

Maximum unique pages to analyze.

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

Preserve parsed nodes and block text rather than compact evidence only.

## `timeoutSecs` (type: `integer`):

Network timeout for each page request.

## `concurrency` (type: `integer`):

Maximum public pages fetched in parallel.

## Actor input object example

```json
{
  "urls": [
    "https://apify.com"
  ],
  "maxPages": 100,
  "includeRaw": true,
  "timeoutSecs": 20,
  "concurrency": 5
}
```

# Actor output Schema

## `dataset` (type: `string`):

No description

## `summary` (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 = {};

// Run the Actor and wait for it to finish
const run = await client.actor("gifted_wagon/json-ld-schema-evidence-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 = {}

# Run the Actor and wait for it to finish
run = client.actor("gifted_wagon/json-ld-schema-evidence-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 '{}' |
apify call gifted_wagon/json-ld-schema-evidence-extractor --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,gifted_wagon/json-ld-schema-evidence-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/EkPFex2qwuP3fFszl/builds/eJDTecdOB0Kzfhveh/openapi.json