Thunderbit

Thunderbit turns webpages into structured tables without making you inspect HTML or write selectors. Open a page in Chrome, select AI Suggest Fields, review the proposed columns, and run the scrape. On a business directory, it might identify the company name, contact details, category, and website. On a shop, it can collect product names, prices, ratings, images, and availability.

You can rename columns, remove unwanted fields, or add written instructions for each column. Thunderbit can extract, summarize, classify, translate, format, and calculate values while it collects the rows. This is useful when the information you need is spread across several parts of a page or needs cleaning before export.

Thunderbit handles more than single page jobs. It can work through pagination and infinite scroll, process a list of URLs, and visit linked subpages. You could scrape a directory first, then ask it to open every company profile and add addresses or employee counts to the original table.

Browser mode works with pages you are already authorized to view through your logged in Chrome session. This covers internal tools, membership sites, and personalized pages. Cloud mode runs public scraping jobs away from your computer and can process several pages concurrently.

There are templates for commonly scraped websites and scheduled jobs for monitoring prices, stock levels, listings, and competitor pages. Results can be downloaded as Excel, CSV, or JSON, or sent directly to Google Sheets, Airtable, and Notion. Thunderbit can also extract information from PDFs and images using OCR.

Developers can access the extraction system through an API, command line tool, and open source MCP server. The MCP package lets compatible AI assistants convert webpages to Markdown, suggest fields, run structured extraction, and submit batch jobs.

The simple setup works well on tidy pages, but web scraping remains unpredictable. Dynamic websites, unusual layouts, expired sessions, anti bot systems, and long pagination runs can cause missing rows or stopped jobs. Test a representative sample before committing credits to a large scrape.

Thunderbit sends the selected page HTML to its servers and Google Gemini for processing. Its privacy policy states that page content is discarded after extraction and is not used for training. Extracted results remain in your account until you delete them. You are still responsible for ensuring that any collection complies with the source website’s terms and relevant privacy laws.

Public feedback is mixed. Users regularly mention the time saved on contact, product, and pricing extraction. Recurring complaints concern fast credit consumption, incomplete large scrapes, billing clarity, refunds, and support response times.

A free plan covers a limited number of pages each month. Paid tiers add subpage extraction, bulk jobs, pagination, enrichment, recurring schedules, higher limits, and additional credits.

🛠️ Thunderbit: Pros & Cons

| Pros (The Wins) | Cons (The Friction) |

| :--- | :--- |

| Setup: AI suggests useful fields. No selectors or code needed. | Credit use: Some reviewers report unexpectedly fast usage. |

| Extraction: Handles pagination, subpages, PDFs, and images. | Long jobs: Large scrapes may stop or return incomplete rows. |

| Export options: Send tables to Sheets, Airtable, or Notion. | Support: Some reviews mention slow billing and refund help. |

Features

AI field suggestions based on page content
Natural language instructions for individual columns
Browser and cloud scraping modes
Pagination and infinite scroll support
Subpage scraping and table enrichment
Bulk scraping from URL lists
Scheduled website monitoring
Templates for frequently scraped websites
PDF and image extraction with OCR
Summarization, classification, translation, and formatting
Excel, CSV, JSON, Google Sheets, Airtable, and Notion exports
Email, phone number, and image extraction tools
API, command line, and MCP access