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Firecrawl

Transforms any website into clean data ready for LLMs. Firecrawl scrapes and returns clean markdown or JSON to feed ChatGPT, Claude or your custom AI apps. Perfect for building RAG systems and knowledge bases.

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Who's it for?OpsGrowth

Review by a Growth Engineer

My verdict: the game-changer for feeding your AI projects with web content.

Firecrawl transforms any website into clean data ready for LLMs. It scrapes a site and returns clean markdown/JSON, perfect for feeding ChatGPT, Claude or your custom AI.

The tool handles JavaScript, cleans HTML, and structures data. Starting at $20/month for 500 pages.

What I like less: the free plan is too limited for a real test. And if you're not doing AI, it's overkill — Puppeteer or Scrapy will do better for classic scraping.

My advice: if you're building AI apps that need web content, Firecrawl is a game-changer. Still young but promising.

Why add it to your stack?

Firecrawl solves a specific problem: transforming web content into data consumable by LLMs. When I build AI agents or RAG systems, I need clean data — Firecrawl does exactly that.

The tool handles JavaScript, cleans messy HTML, and structures data. It's the missing link between the web and my AI apps.

What you can do with it

  • 1Feed a RAG chatbot with documentation content
  • 2Scrape sites to train or fine-tune models
  • 3Build knowledge bases from websites
  • 4Create datasets for AI projects
  • 5Automate content extraction for LLM analysis

What it does

  • Web scraping optimized for LLMs
  • Output in markdown or structured JSON
  • JavaScript and dynamic content handling
  • Automatic HTML cleaning
  • Simple REST API
  • Full site crawling

How much?

Starting at $20/month

Limited free plan (100 pages). Hobby at $20/month (500 pages). Standard at $50/month (2000 pages). Scale from $200/month.

The detailed verdict

Do I really need this?

For AI projects that need web data, Firecrawl quickly becomes indispensable. It's the bridge between the web and your LLMs.

If you're not doing AI, the tool is overkill. But for builders working with GPT/Claude, it's a game-changer.

Does it play nice with my stack?

The API is excellent — simple, well documented, with SDKs for popular languages. Integration into n8n, Make, or your custom scripts is straightforward.

Compatible with popular AI frameworks (LangChain, etc.). It's designed for developers.

Is it easy to pick up?

Getting started is quick for simple cases. You call the API with a URL, you get your markdown back. In 10 minutes, you have your first data.

For advanced use (full crawling, filters), the curve is a bit steeper. Docs are decent but could use more examples.

Is the UX any good?

Interface and API are well designed. You send a URL, you get clean markdown back. No complex configuration for simple cases.

For more sophisticated crawls (full sites, filters), you need to dive into the docs. The tool is still young but iterates quickly.

Is it worth it?

At $20/month for 500 pages, it's reasonable for AI projects. The free plan (100 pages) lets you test but remains limited. For intensive use, Scale plans are necessary.

Compared to development time for a custom scraper that handles JS and cleans HTML, Firecrawl pays for itself quickly.

What I like

  • Excellent for feeding LLMs with clean web content
  • Perfect for AI apps and RAG (Retrieval Augmented Generation)
  • Ideal for developers building with AI

What I like less

  • Not suited for classic scraping without AI as Puppeteer or Scrapy are better
  • Overkill for projects without an AI component
  • Free plan is too limited for a real test

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