AI Web Extract — Structured Data from Any URL (Firecrawl Extract Alternative)

Give it a URL, get back clean structured JSON — no LLM, no API key, no browser. AI Web Extract is a fast, keyless Firecrawl Extract alternative built for AI agents, RAG pipelines and MCP workflows. Point it at any web page and it pulls every structured signal already baked into the HTML — schema.org JSON-LD, OpenGraph / Twitter / meta, microdata, tables, headings, images, contacts, prices and dates — and returns them as one tidy JSON record per URL. Most web scraping tasks don't need a browser or a language model: product pages, articles, recipes, events, business listings and news already ship rich, machine-readable structured data in their markup, and this actor harvests it directly — deterministically, cheaply, and without burning LLM tokens guessing at fields.

🏆 Why this web extractor?

17 structured fields per URL · batch up to 500 URLs in one run · no API key, no LLM, no browser · deterministic JSON-LD & OpenGraph parsing (zero hallucinations) · pay only per extracted page · unofficial Firecrawl Extract API alternative · export to JSON / CSV / Excel

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✨ What this Actor does / Key features

• 📦 Structured JSON, not raw HTML — skip the parsing. Get jsonLd, openGraph, tables, prices, contacts and a flattened extracted object your agent can use immediately.
• 🔑 Keyless & cheap — no third-party API key, no LLM inference cost. Plain HTTP over Apify's datacenter proxy keeps it fast and inexpensive — a true web scraping API for structured data.
• 🎯 Deterministic, zero hallucinations — JSON-LD and OpenGraph parsing is exact and repeatable. No prompt tuning, no invented values.
• 🧩 schema.org JSON-LD extractor — parses every application/ld+json block, @graph-flattened and malformed-JSON tolerant (Product, Article, Recipe, Event, Organization, BreadcrumbList…).
• 💲 Smart price detection — reads JSON-LD offers first for accuracy, then multi-currency regex heuristics across 25+ currencies.
• 📊 Tables → row objects — every HTML <table> becomes an array of row objects with the header row as keys.
• 📇 Contact harvesting — pulls emails and phone numbers (mailto:, tel: and text heuristics) for lead enrichment.
• 🤖 Agent-native (MCP) — pay-per-event pricing means an AI agent can call it, pay per page, and move on — no account juggling.
• ⚡ Batch or single — extract one URL or up to 500 in a single run with configurable concurrency (1–20).
• 🧪 Firecrawl Extract alternative — covers the core "URL → structured JSON" job without vendor lock-in or per-key billing.

🚀 Quick start (3 steps)

1. Configure — paste one or more URLs into URLs (or a single URL into Single URL). Optionally list the exact fields you want back and toggle the extraction blocks.
2. Run — click Start. Each page is fetched over Apify proxy and turned into a structured record; runs are fast because there's no browser and no LLM.
3. Get your data — every URL streams to the dataset as one JSON record. Export as JSON, CSV, Excel, HTML table or RSS, or pull it live via the Apify API.

📥 Input

The only required input is at least one URL — either a batch list in URLs or a single value in Single URL. Everything else is optional and shapes the output.

Scenario A — extract product data for price monitoring

{
  "urls": [
    "https://www.apple.com/shop/buy-iphone/iphone-16-pro"
  ],
  "fields": ["price", "brand", "rating"],
  "extractJsonLd": true,
  "extractTables": true
}

Scenario B — batch article & metadata harvesting for RAG

{
  "urls": [
    "https://en.wikipedia.org/wiki/Anthropic",
    "https://en.wikipedia.org/wiki/Retrieval-augmented_generation"
  ],
  "extractJsonLd": true,
  "extractContacts": false,
  "extractImages": false,
  "concurrency": 5
}

Scenario C — lead & contact enrichment from a business page

{
  "url": "https://example-agency.com/contact",
  "extractContacts": true,
  "extractLinks": true,
  "proxyGroups": ["RESIDENTIAL"]
}

Field	Type	Description
urls	array	One or more page URLs to extract structured data from. Batch up to 500.
url	string	A single page URL. Use this or the urls list above.
fields	array	Optional: specific fields you want (e.g. price, author, rating). Best-effort, case-insensitive mapping against JSON-LD, meta and the flattened extracted object, returned under requestedFields. Never fails if a field is missing.
extractJsonLd	boolean	Parse all schema.org <script type="application/ld+json"> blocks. The richest structured source. Default true.
extractTables	boolean	Convert each HTML <table> into an array of row objects (header row → keys). Default true.
extractContacts	boolean	Detect emails and phone numbers (mailto:, tel: and text heuristics). Default true.
extractImages	boolean	Collect in-content images as { alt, url } with absolute URLs. Default true.
extractLinks	boolean	Collect in-content links as { text, url } with absolute URLs (deduped, capped at 100). Default false to keep output lean.
concurrency	integer	How many URLs to fetch in parallel (1–20). Lower for fragile sites. Default 5.
useApifyProxy	boolean	Route requests through Apify datacenter proxy (AUTO). Recommended — avoids per-IP rate limits. Default true.
proxyGroups	array	Override proxy group, e.g. RESIDENTIAL for bot-walled sites. Leave empty for datacenter (AUTO).

📤 Output

Each URL produces exactly one dataset record — even a failed fetch produces a row (with an error) so nothing is silently dropped. Below is a realistic trimmed record:

{
  "url": "https://www.apple.com/shop/buy-iphone/iphone-16-pro",
  "finalUrl": "https://www.apple.com/shop/buy-iphone/iphone-16-pro",
  "statusCode": 200,
  "title": "Buy iPhone 16 Pro and iPhone 16 Pro Max",
  "extracted": {
    "title": "iPhone 16 Pro",
    "description": "iPhone 16 Pro. Built for Apple Intelligence.",
    "price": "999",
    "currency": "USD",
    "brand": "Apple",
    "image": "https://www.apple.com/v/iphone-16-pro/a/images/overview/hero.jpg"
  },
  "jsonLd": [
    {
      "@type": "Product",
      "name": "iPhone 16 Pro",
      "offers": { "@type": "Offer", "price": "999", "priceCurrency": "USD" }
    }
  ],
  "openGraph": { "og:title": "iPhone 16 Pro", "og:type": "product" },
  "meta": { "description": "iPhone 16 Pro. Built for Apple Intelligence.", "lang": "en-US" },
  "headings": ["iPhone 16 Pro", "Tech specs"],
  "prices": [{ "value": 999, "currency": "USD", "raw": "999" }],
  "contacts": { "emails": [], "phones": [] },
  "requestedFields": { "price": "999", "brand": "Apple", "rating": null },
  "fetchedAt": "2026-07-06T09:14:22.183Z"
}

💡 Use cases

• AI agent "extract from URL" tool — give an agent a structured-data tool it can call mid-conversation and pay per page.
• E-commerce & price monitoring — pull product name, price, currency, availability and rating from any product page via its JSON-LD offers.
• RAG & knowledge bases — ingest clean structured facts (not noisy HTML) before chunking and embedding.
• Content & metadata harvesting — grab titles, authors, publish dates and OpenGraph cards for articles and news at scale.
• Lead & contact enrichment — extract emails, phones and organization data from business pages.
• Comparison & aggregation — normalize tables and specs across many sources into consistent JSON.

👥 Who uses it

AI agent builders · RAG / LLM engineers · MCP tool authors · e-commerce & price-intelligence teams · growth & lead-gen ops · data engineers · researchers & analysts

💰 Pricing

This actor uses Apify's pay-per-event model: you're charged once per extracted URL — one result event per page. No monthly fee and no idle cost, so an AI agent can call it, pay per page, and move on. See the Pricing tab on the actor's Apify page for current per-event rates. You also pay standard Apify platform usage for the run.

❓ Frequently Asked Questions

Is this a Firecrawl Extract API alternative?

Yes. It covers the core "URL → structured JSON" job Firecrawl Extract is used for — pulling specific fields and schema.org data from a page — without requiring an API key or an LLM. You run it on Apify and pay per extracted page.

Can I use it without an API key or login?

Yes. It's fully keyless and works out of the box using Apify's datacenter proxy — no third-party API key, no account juggling, no login. Switch to RESIDENTIAL proxy only for bot-walled sites.

Does it use an LLM?

No. Extraction is deterministic: it parses JSON-LD, OpenGraph, microdata, tables and prices straight from the HTML. That makes it faster, cheaper and free of hallucinated values. Use the optional fields input to name what you want back under requestedFields.

How do I export the data to CSV or JSON?

Every run writes to an Apify dataset that exports to JSON, CSV, Excel (XLSX), HTML table or RSS in one click — or pull it live via the Apify API. It doubles as a structured web-data export and dataset tool.

Is it legal?

It reads publicly available page markup (JSON-LD, OpenGraph, meta, visible HTML) over plain HTTP — the same data any browser or search engine crawler sees. You are responsible for complying with each site's Terms of Service and applicable privacy laws (GDPR, CCPA) when processing extracted data. This actor is not affiliated with Firecrawl or any site it reads.

How much data can I get?

Batch up to 500 URLs per run, tune concurrency (1–20) for throughput, and schedule repeated runs for continuous extraction. Each URL always yields one record, so volume scales linearly with your URL list.

What kinds of pages work best?

Anything with structured markup — product pages, articles, recipes, events, job posts, business listings, news. The more schema.org JSON-LD or OpenGraph a page ships, the richer the output. Pages with no structured data still return meta, headings and tables.

Does it render JavaScript?

No — it reads server-rendered HTML over plain HTTP, which keeps it fast and cheap and covers the vast majority of pages (JSON-LD and OpenGraph are almost always in the initial HTML). For heavy client-rendered apps, use a browser-based scraper.

How are prices detected?

JSON-LD offers (price + priceCurrency) are read first for accuracy, then visible-text regex heuristics catch formats like $1,299.00, €49, £9.99, 1 299,00 € and USD 49 across 25+ currencies.

Can I use it as an MCP tool?

Yes. Because it's pay-per-event, AI agents can discover and call it autonomously through the Apify MCP server — one charge per extracted URL. Connect it in Claude, Cursor or any MCP client. It pairs naturally with a "read this page" Markdown tool: use Markdown for prose, use AI Web Extract when you need fields (price, rating, author, dates).

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Company Deep Research Scraper	Compile a structured company dossier from the open web.
Semantic Scholar Research Scraper	Academic papers, authors and citation graphs.
arXiv Paper Scraper	Harvest arXiv paper metadata and abstracts.
News Intelligence Scraper	Multi-source news monitoring and extraction.
GitHub Repository Scraper	Structured repo, README and metadata extraction.
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👉 Browse all logiover scrapers on Apify Store — 180+ actors across real estate, jobs, crypto, social media & B2B data.

⏰ Scheduling & integration

Schedule the actor on Apify to re-extract a URL list on any cadence, and export results to JSON, CSV, Excel or RSS. Wire it into Google Sheets, Airtable, Notion, Slack, a data warehouse or your own backend using the Apify API, webhooks, or no-code tools like Make, n8n and Zapier. Because it's pay-per-event and MCP-ready, AI agents can also call it on demand — one charge per extracted page.

⭐ Support & feedback

Found a page that didn't parse the way you expected, or want a new extraction block? Open an issue on the actor's Issues tab with the URL. If this actor saves you time, a ★★★★★ review on the Apify Store genuinely helps others find it and helps us keep improving it.

⚖️ Legal

AI Web Extract reads publicly available page markup — schema.org JSON-LD, OpenGraph / Twitter / meta tags and visible HTML — over plain HTTP, exactly the data a browser or search-engine crawler already sees. It does not bypass logins, paywalls or authentication. You are responsible for using extracted data in compliance with each source site's Terms of Service and applicable data-protection laws (GDPR, CCPA and similar). This actor is not affiliated with Firecrawl or any website it reads.

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📝 Changelog

2026-07-06

• ✨ README overhaul: richer output sample, ready-to-run example scenarios, cross-promo links, and clearer quick-start.

1.0 (2026-07-04)

• Initial release.
• Keyless structured-data extraction from any URL — a Firecrawl Extract alternative for AI agents, RAG and MCP. No LLM, no API key, no browser.
• Extracts per URL: schema.org JSON-LD (all blocks, @graph-flattened, malformed-JSON tolerant), OpenGraph/Twitter/meta, microdata (itemscope/itemprop), headings (h1/h2/h3), tables (row objects with header keys), in-content images and links (absolute URLs), contacts (emails + phones), and prices (JSON-LD offers first, then multi-currency regex heuristics).
• Flattened extracted convenience object (title, description, price, currency, brand, author, publishedDate, ratingValue, image) merged from JSON-LD/OpenGraph.
• Optional fields input for best-effort, case-insensitive field mapping returned under requestedFields.
• Batch or single URL, configurable concurrency, Apify datacenter proxy by default (RESIDENTIAL opt-in).
• Pay-per-event: one result charge per extracted URL. Every URL — even a failed one — produces a dataset row.