How to Scrape Any Website Without Code Using Thunderbit AI

Web scraping used to be a coder’s job.

You needed Python, CSS selectors, XPath, proxies, and the patience to fix a broken scraper every time a website changed its layout.

 For most marketers, founders, and researchers, that was a wall. The data was right there on the screen, but getting it into a spreadsheet meant hiring a developer or giving up.

In 2026, that wall is gone.

AI web scrapers now read a page the way a human does, understand what the data means, and pull it into clean rows in seconds. No code. No selectors. No fixing broken scripts at midnight.

This guide shows you exactly how to do it, step by step, using the tool I settled on after testing the whole market: Thunderbit. By the end, you will be able to scrape leads, prices, jobs, listings, or almost anything else from any website, and send it straight to Google Sheets.

Let us get into it.

What Is Web Scraping (In Plain English)

Web scraping means automatically collecting information from websites and organizing it into a structured format like a spreadsheet.

Instead of copying and pasting 500 business names, phone numbers, and addresses by hand, a scraper grabs all of them in seconds and drops them into neat rows and columns.

That is it. That is the whole idea.

The data you can scrape is everywhere: product listings, prices, reviews, real estate listings, job posts, business directories, social media profiles, contact details, and more. If you can see it on a web page, a modern scraper can usually pull it.

The old way needed code. The new way needs a click.

Why No-Code AI Scrapers Changed Everything

Traditional scrapers, and even some popular ones today, work with CSS selectors. You had to tell the tool exactly where each piece of data lived in the page’s HTML. Build a scraper for one site, and it would break the moment that site changed its design. Move to a new site, and you built the whole thing again.

AI web scrapers flipped this completely.

Now you just describe what you want in plain language. You type the column names you need, like “Name,” “Email,” “Price,” or “Job Title,” and the AI reads the page, understands the content, and fills those columns for you.

No selectors. No HTML. No rebuilding for every site.

This is the shift that made scraping accessible to everyone, not just developers. And it is why I moved a big chunk of my client data work to this approach.

Meet Thunderbit: The AI Web Scraper I Actually Use

I have tried a lot of scrapers. Octoparse and Firecrawl are still favorites of mine for certain jobs, and I have tested Browse AI too. Each has its place.

But when a client needs data extracted fast, with zero technical setup, Thunderbit is the one I reach for now.

Thunderbit is an AI web scraper that runs as a Chrome extension and claims to scrape data in two clicks. After four months of real use, I can tell you that claim mostly holds up. It is genuinely that fast for most pages.

A few things make it stand out:

It is trusted at scale as well. Thunderbit reports around 200,000 users, including people at Harvard, MIT, Adidas, BCG, and Wix, and it was a #1 Product of the Week on Product Hunt. That is not why you should use it, but it tells you the tool is real and maintained.

Step-by-Step: How to Scrape Any Website Without Code

Here is the exact process. I will keep it simple, because the tool is simple.

Step 1: Install the Thunderbit Chrome Extension

Head to Thunderbit and add the extension to Chrome. It installs in a few seconds, and you sign up with a free account.

Once installed, you will see the Thunderbit icon in your browser toolbar. That is your scraping button from now on.

Step 2: Open the Page You Want to Scrape

Navigate to any website you want data from. A business directory, a real estate site, a job board, a product category page, anything.

Let the page fully load. If it is a list (search results, listings, products), scroll a little so the content is there.

Then click the Thunderbit extension icon to open the panel.

Step 3: Click “AI Suggest Fields”

This is the magic step.

Instead of telling Thunderbit where each piece of data is, you click AI Suggest Fields. The AI reads the page and automatically proposes the columns it thinks you want, things like Name, Price, Rating, Address, or Email, depending on the page.

In most cases, it nails the structure on the first try. You get a ready-made table layout without lifting a finger.

Step 4: Adjust Your Columns (Optional)

If you want something specific, just type it.

Add a column, name it whatever you want (“Owner Name,” “Phone,” “Reviews Count”), and set the data type. You can even give the AI an instruction for a column, like “extract only the mobile number” or “summarize the description in 10 words.”

This is where the natural-language power shows. You are describing the output you want in your own words, and the AI handles the extraction logic.

Here are a few example column setups I use:

Column: Business Name    → Type: Text
Column: Phone            → Type: Text (instruction: mobile only)
Column: Email            → Type: Text
Column: Rating           → Type: Number
Column: Summary          → Type: Text (instruction: summarize in 10 words)

Step 5: Click “Scrape”

Now the second click. Hit Scrape, and Thunderbit fills your table with clean, structured data from the page.

Rows appear in seconds. What would have taken hours of copy-paste, or a custom script, is done.

Step 6: Scrape Subpages (When You Need Detail)

Sometimes the list page does not have everything. The good data lives on each item’s detail page.

Thunderbit handles this with subpage scraping. It can visit each linked page, pull the deeper details (like a full description, contact info, or specs), and add them to your rows automatically.

So you can scrape a directory list, then have Thunderbit open each business’s page and grab the email and phone that were not on the main list. All in one flow.

Step 7: Export to Google Sheets (or Anywhere)

Finally, send your data where you work.

One click exports to Google Sheets, Airtable, or Notion, or downloads as CSV or Excel. No formatting cleanup, no messy paste. It lands ready to use.

That is the whole method. Install, open, suggest fields, scrape, export. Two real clicks for most jobs.

Beyond Web Pages: Documents, PDFs, and Images

Most scrapers stop at web pages. Thunderbit does not.

It can extract structured data from documents, PDFs, and images too. So if your data lives in a PDF report, a scanned table, or an image, the same AI can read it and give you rows.

For research, invoices, catalogs, and reports, this is a genuinely useful extra that saved me real time.

For Builders: The Thunderbit API and MCP

Here is the part developers and SaaS builders will care about.

Thunderbit is not only a Chrome extension. It offers a Web Scraper API, plus CLI and an MCP server.

The API means you can build scraping directly into your app’s backend. If you are building a SaaS, a directory, or an AI project that needs live web data, you call the API and get structured results.

And because it has an MCP server, you can connect it to AI agents like Claude. Using Claude Code, wiring Thunderbit into a project can be done very fast, so an agent can scrape on demand as part of a bigger automated workflow.

So Thunderbit scales from “beginner clicking a button” all the way to “developer building it into production.” That range is rare.

Scheduled Scraping: Set It and Forget It

You can also schedule scrapes to run automatically.

Point Thunderbit at a page, set a schedule (daily, weekly), and it collects fresh data on its own. For price monitoring, new job listings, or tracking changes, this turns a one-time scrape into an always-on data feed.

Thunderbit Pricing 2026: Is It Worth It?

Here is the honest pricing breakdown, because value matters.

Thunderbit runs on a credit system, and one output row equals one credit. That is easy to reason about: 1,000 rows costs 1,000 credits.

Plan	Price	Credits	Best For
Free	$0 forever	30 credits/page, 6 pages/month	Trying it out
Pro (annual)	~$16.50/mo billed yearly	~30,000 credits for the year	Best value, regular use
Pro (monthly)	~$38/mo	3,000 credits/month	Flexible, no commitment
Business	Custom	Custom credits and limits	Teams, high volume

A few honest observations from paying for it myself.

Is it the absolute cheapest? Not always. If you are doing pure high-volume scraping through an API, something like Firecrawl’s API can work out cheaper per page for certain jobs. I use Firecrawl too, and I am not going to pretend otherwise.

But that misses the point of Thunderbit. You are paying for no-code speed plus AI structuring. For anyone who does not want to write code, or who values pulling clean, ready-to-use rows in two clicks across any site, Thunderbit’s pricing is genuinely cost-effective. Match the tool to the job.

Tips to Get Better Scraping Results

A few things I learned that make no-code scraping smoother:

FAQs Related to Thunderbit Website Scraping

Final Thoughts: Scraping Is a Skill Anyone Can Have Now

For years, web scraping was gatekept behind code. If you could not write Python, the data stayed out of reach.

That era is over.

With an AI scraper like Thunderbit, extracting data from any website is a two-click skill. Install the extension, let the AI suggest your fields, scrape, and export. Whether you are gathering leads, tracking prices, building a job board, or feeding data into an AI project, the barrier is gone.

I tested a lot of tools to arrive here. Octoparse and Firecrawl still earn their place in my stack, and I told you honestly where each fits. But for fast, no-code, AI-powered scraping across almost any site, Thunderbit is the one I keep coming back to, and the one I recommend to beginners without hesitation.

The best part: you can start free and prove it to yourself in the next ten minutes.