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Planned, not doneThe source describes an intention, not a finished result.

Turn public competitor pages into a structured market scan with Crawl4AI

Crawl4AI crawls pages into clean Markdown and extracts fields such as product names and prices with CSS or XPath schemas or an LLM, giving an agent tidy input for a market or competitor comparison.

Try the promptRead the original (opens in a new tab)

The problem

How it works

Crawl4AI is an Apache-2.0 Python crawler aimed at LLM pipelines. It renders pages in a real browser and outputs Markdown, or filtered Markdown with menus and footers removed. Structured data can be pulled without an LLM using CSS, XPath or regex schemas, or with an LLM into a JSON schema through any LiteLLM provider, including a local Ollama model. Deep crawls follow links breadth-first, depth-first or best-first, and a Docker server exposes a REST API and an MCP option.

Results and limitations

The README documents features and examples rather than a measured outcome. It also promotes a hosted cloud API alongside the self-hosted open-source crawler.

Before you try it

Crawl only public pages, keep request rates low, and check each site's robots rules and terms yourself, since the README does not describe how robots.txt is handled. Do not use the stealth or undetected-browser options to get past a site's bot protection. Prices can vary by region and session, so check key numbers on the live page. The README asks for attribution through a badge or text line when you use the project. Results depend on your setup and were not independently reproduced by Top 200 Repos.

Tools and repositories

Tools
Crawl4AI (pip or Docker) · Optional LLM through LiteLLM, such as a local Ollama model
Prerequisites
Python with pip and a Playwright browser installed by crawl4ai-setup, or Docker; an LLM key only for LLM extraction.

Try it yourself: Compare competitor offers from crawled pages

Fill the fields to adapt the prompt. Empty fields stay as visible [placeholders].

Preview
Here is Markdown or JSON that Crawl4AI extracted from these public pages: [Extracted page content]. Build a comparison table for [Product category] with one row per product: company, product name, listed price and currency, billing period, key features and the source URL. Leave a cell empty and mark it unclear when the page does not state a value, instead of guessing. Then summarise in five bullet points how these offers compare with [Your offer]. Use only the supplied content, and list any page that looked incomplete so I can check it by hand.

Verify prices on the live pages before sharing the comparison.

Related videos

About unclecode/crawl4ai

About ollama/ollama

Independent creators. Listing a video implies no endorsement, sponsorship or partnership.

Sources

  1. unclecode/crawl4ai README (opens in a new tab)

    Project documentation · github.com · Undated · Source checked 12 Nov 2026, 03:31 UTC

    What this source supports
    • Turns web pages into clean Markdown and filtered fit Markdown for LLMs
    • Extracts structured data with CSS, XPath or regex schemas without an LLM, or with an LLM into a JSON schema
    • LLM extraction works with any LiteLLM provider, with Ollama given as an example
    • Deep crawling with BFS, DFS and best-first strategies; Docker server with REST API and MCP option
    • Apache-2.0 licence with an attribution request; latest release v0.9.5
Report a problem

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