# URL to JSON - Web Page Metadata, Headings & Text Extractor (`timely_quarterstaff/datapulse-url-extractor`) Actor

Turn any public URL into structured JSON: title, meta tags, headings, links, JSON-LD and clean readable text with a code-computed summary. Deterministic and SSRF-guarded, with optional AI enrichment you control.

- **URL**: https://apify.com/timely_quarterstaff/datapulse-url-extractor.md
- **Developed by:** [Ahmed Moussa](https://apify.com/timely_quarterstaff) (community)
- **Categories:** Developer tools
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$1.00 / 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.

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

## DataPulse URL Extractor

Deterministic, SSRF-guarded structured-data extraction from any public URL.

### What it does

For each input URL the actor returns a single dataset item with:

- `url` — the requested URL
- `status` — `completed`, `blocked`, `failed`, or `empty`
- `data` — structured extraction: `title`, `meta_tags`, `headings`, `links`, `text`
  (and, when AI enrichment is enabled, an `ai_extracted` block)
- `meta` — **code-owned, deterministic**: `extracted_at` (real server time),
  `method`, and a `summary` (`row_count`, numeric stats) computed in code from
  the extracted data — never trusted from any model.

### Input

```json
{
  "url": "https://example.com",
  "urls": ["https://www.iana.org/help/example-domains"],
  "schema_hint": "company info",
  "llm_api_key": "(optional — enables AI enrichment)",
  "llm_model": "deepseek/deepseek-chat"
}
```

`url`/`urls` are public http(s) URLs. If `llm_api_key` (or the `OPENROUTER_API_KEY`
secret) is empty, the actor returns a fully deterministic, code-only extraction.

### Output

One JSON item per URL pushed to the default dataset:

```json
{
  "url": "https://example.com",
  "status": "completed",
  "data": {
    "title": "Example Domain",
    "meta_tags": { "description": "..." },
    "headings": [ { "level": "h1", "text": "Example Domain" } ],
    "links": [ { "href": "https://www.iana.org/domains/example", "text": "More information..." } ],
    "text": "Example Domain This domain is for use in..."
  },
  "meta": { "extracted_at": "2026-06-23T00:00:00+00:00", "method": "deterministic_code", "summary": { "row_count": 1 } }
}
```

### Use cases

- Turn an arbitrary public page into clean, structured JSON for a pipeline or LLM prompt.
- Pull title / meta / headings / links / body text for SEO, monitoring or content audits.
- Lightweight "fetch + parse" step that is safe to run on untrusted URLs (SSRF-guarded).

### How it works (deterministic, code-only)

Pure code: HTTP fetch through an SSRF-guarded client, then stdlib/regex HTML parsing
to extract title, meta tags, headings, links and clean text. The `meta.summary` is
computed in code from the parsed data. No headless browser, no AI on the default path.

### Safety (always on)

- **SSRF guard** — any URL that resolves to a private / loopback / link-local /
  reserved address is **blocked** (fail-closed); each redirect hop is
  re-validated before being followed.
- **Blocklist** — login-walled / ToS-sensitive domains (LinkedIn, Facebook,
  Instagram, X, Glassdoor, Indeed, Zillow, Yelp, …) are refused.
- **Bounded fetch** — 5s connect / 10s read timeout, 2 MB hard size cap,
  content-type allowlist, max 3 redirects. Never crashes or hangs.

### Limitations (honest)

- Pages that render entirely client-side (heavy JS, no server-side HTML) expose
  less content — there is no headless browser on the default path.
- Login-walled / blocklisted domains return `status: "blocked"` by design.
- AI enrichment requires **your own** OpenRouter key; the actor ships no built-in key.

***

Powered by OMEGA · DataPulse extraction core.

# Actor input Schema

## `url` (type: `string`):

A single public URL to extract structured data from.

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

Optional list of additional URLs to extract (processed in addition to 'url').

## `schema_hint` (type: `string`):

Optional. What data to focus on (e.g. 'company info', 'product listings'). Only used when AI enrichment is enabled.

## `llm_api_key` (type: `string`):

Optional. Enables AI enrichment of the deterministic extraction. If empty, a fully deterministic code-only extraction is returned.

## `llm_model` (type: `string`):

OpenRouter model id for AI enrichment.

## Actor input object example

```json
{
  "url": "https://news.ycombinator.com",
  "llm_model": "deepseek/deepseek-chat"
}
```

# 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 = {
    "url": "https://news.ycombinator.com"
};

// Run the Actor and wait for it to finish
const run = await client.actor("timely_quarterstaff/datapulse-url-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 = { "url": "https://news.ycombinator.com" }

# Run the Actor and wait for it to finish
run = client.actor("timely_quarterstaff/datapulse-url-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 '{
  "url": "https://news.ycombinator.com"
}' |
apify call timely_quarterstaff/datapulse-url-extractor --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,timely_quarterstaff/datapulse-url-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/1fwkDpAbO6SpWsGFz/builds/NwdRiy7pw5av2SLWU/openapi.json