MacLaren Scott

Posted on Dec 8

Crawler Comparison: Firecrawl Alternative with Headful Chrome for Web Crawling and Browser Automation

#tooling #automation #javascript #ai

If you’ve tried to scrape the modern web in 2025, you already know the story: more JavaScript, more React, more bot protection, and fewer pages that “just work” with simple HTML fetches. Modern web servers often require sophisticated handling of HTTP requests to retrieve content, especially from complex websites. Traditional browser automation tools often suffer from broken scripts when websites change their structure, leading to high maintenance and frequent updates. AI-powered solutions can minimize maintenance and automatically adapt to website changes, significantly reducing ongoing effort compared to traditional methods.

Teracrawl is our answer to that problem.

Teracrawl is web automation software designed to handle modern, dynamic sites. Instead of pretending that the web is static, Teracrawl runs on real Chrome browsers powered by the Browser.cash network. That means it behaves like an actual user’s browser—loading JavaScript apps, calling APIs, dealing with lazy-loaded components, and surviving the basic anti-bot checks that break traditional scrapers. By rotating IP addresses, Teracrawl helps avoid detection and enables reliable extraction from many websites, even those with strict anti-bot measures. Teracrawl delivers powerful automation, enabling complex, reliable, and adaptive workflows for dynamic web environments. Teracrawl can extract information from complex websites at high volume, supporting live data needs for enterprise users.

Teracrawl also offers advanced features that set it apart for enterprise-level automation, making it especially suitable for large organizations seeking comprehensive browser automation solutions. It leverages artificial intelligence and machine learning to adapt to website changes and optimize data extraction workflows.

In This Post, We’ll Cover

What Teracrawl is and how it works with Browser.cash
Why headful browsers matter vs. headless/HTML-only scrapers
Concrete examples where Teracrawl succeeds and Firecrawl doesn’t
How this fits into LLM/RAG and agentic workflows
How Teracrawl supports browser-based workflows that automate complex tasks directly in the browser
How Teracrawl supports business process automation

What Teracrawl Is

Teracrawl is an open-source crawler that takes URLs and turns them into LLM-ready content. As a web crawler, it can automatically navigate and extract data from multiple pages across many sites, making it ideal for large-scale data collection:

Clean markdown or HTML
Extracted main content (tables, catalogs, search results)
Minimal boilerplate (no endless navs, cookie banners, or tracking junk)

Scraping tools and custom scripts written in various programming languages can be used to further process or analyze the extracted data.

As a free and open source project, Teracrawl benefits from community support, making it easier for users to get help, share solutions, and contribute improvements.

Under the hood, it doesn’t talk directly to Chromium. Instead, it uses the Browser.cash** browser network** as a backend:

Teracrawl orchestrates crawls, sessions, retries, and extraction
Browser.cash provides pools of real, managed Chrome browsers that actually visit each page

The result is a crawler that behaves like “a lot of users in a lot of browsers” instead of “one big headless script in a data center.”

Because Browser.cash is a network of browser nodes, Teracrawl can scale across many machines and fingerprints, rather than hammering websites from a single headless cluster. Teracrawl can efficiently scrape sites at scale, access web data from dynamic and complex sources, and interact with application programming interfaces (APIs) when available.

Why Headful Browsers Matter for Browser Automation Tools

Most scraping engines today fall into one of two camps:

Static / HTML-only\
Fetch HTML and maybe run a lightweight renderer. Works for simple blogs/docs. Most web pages are built with HTML and require specialized web scraping tools to extract data accurately.
Headless browser clusters\
Spin up Chrome in the cloud, but often share identical fingerprints/IPs—easy to detect.

Some browser automation solutions also come as Chrome extensions, offering no-code interfaces, but they typically lack robustness for complex scraping. There are also platforms that require no coding required and can export data directly to Google Sheets for further analysis.

Modern web challenges include:

React/Next/Vue SPAs that only render after hydration
JSON/GraphQL APIs hidden behind UI logic
Anti-bot systems detecting obvious automation
Infinite scroll, requiring scraping tools that can handle dynamically loaded content

This often leads to scrapers returning only headers/skeleton UIs—no data. CSS selectors are commonly used to target specific elements for extraction, and the output is often delivered in a structured format like CSV or JSON.

Teracrawl avoids this entirely:

Runs real headful Chrome
Uses the Chrome DevTools Protocol for fast, reliable control
Sessions run in isolated, real machine instances
Waits for JS to fully load before extraction
Survives basic anti-bot checks

Some advanced tools even use computer vision; Teracrawl is built to support similar capabilities.

Result: Sites that look impossible to scrape become routine.

Real-World Comparison: Teracrawl vs Firecrawl

Firecrawl is solid for static + semi-dynamic content.\
But dynamic JS-heavy sites expose architectural limits.

Below are three URLs where Teracrawl dominated.

1. Yahoo Finance – Currencies

URL:https://finance.yahoo.com/currencies

Page is a React SPA. Data loads after hydration.

Teracrawl is able to extract specific data from the web page, such as currency tables and pricing information, even when content loads dynamically. The crawler fetches and parses the web page, targeting financial tables and other relevant elements for accurate data extraction.

The returned web scraping data includes structured currency rates and related financial information. This data can be used for competitor pricing analysis, market research, or integration into business workflows.

Additionally, you can perform an html save of the extracted content, allowing for further analysis or integration into other systems.

Teracrawl (Browser.cash)

Runs the full React app
Calls the live pricing API
Returns the complete currencies table

Firecrawl

Blocked entirely: “Oops, something happened”
No table, no data

2. AT&T Wireless Phones Catalog

URL:https://www.att.com/buy/wireless/phones

React frontend + JSON APIs. Teracrawl’s approach to extracting product data from the AT&T catalog is also highly applicable to e-commerce websites and other web scraping applications, where automated crawlers are used for collecting data such as product listings, prices, and inventory.

After extracting the product catalog, the structured data can be used for lead generation, collecting data for real estate data analysis, and integrating data from websites into business workflows for automation and decision-making.

Firecrawl

Extracted only header/nav
No product data at all

Teracrawl (Browser.cash)

Fully executed React
Returned complete product catalog

3. GoDaddy Domain Search

URL:https://www.godaddy.com/en-ca/domainsearch/find?domainToCheck=mydomain.io

JS-heavy. Pricing + availability load via front-end logic. Similar browser automation and scraping data techniques can also be used to extract real estate listings from property websites and to monitor online services for changes in features, pricing, or availability.

The returned data includes domain availability, pricing, and related suggestions. Scraping data in this context is valuable for content monitoring, tracking changes in domain ownership, and identifying the parent company behind a domain. This enables businesses to stay updated on market shifts and competitor activity.

Firecrawl

Returned static shell
Zero search results

Teracrawl

Hydrated full React app
Returned pricing, availability, recommendations

Built for LLMs, RAG, Web Data Extraction, and Agents

Teracrawl does more than “load pages.” It produces AI-usable data:

Clean Markdown output
Structured extraction (tables, lists, key-value)
Consistent formatting (good for chunking)
Screenshots for debugging or vision models

This structured website data can be used to train AI models and easily imported into Google Sheets for live, dynamic analysis.

Because of Browser.cash:

Agents can request fresh data anytime, enabling marketing teams to gain deep insights from website data in real time
Hard JS-heavy pages can route through Teracrawl
Browser sessions can be reused and orchestrated at scale

When to Use Teracrawl for Web Scraping Applications

You don’t need a real browser for everything. But you do for the 5–20% of URLs that matter:

Finance dashboards
E-commerce pricing/catalogs
Domain search tools
SaaS dashboards
Any page where scrapers return skeleton UIs

Teracrawl excels at web data extraction and data scraping, especially for complex websites that require advanced automation and reliable data collection.

Teracrawl handles the difficult sites that break other scrapers.

Scraping tools can be used for a few websites with simple requirements, or scaled up to handle large projects involving many sites and complex data extraction workflows.