Firecrawl vs ScrapingBee: Which MCP should you use?
Firecrawl
LLM-ready web scraping API
ScrapingBee
Headless browser scraping API
TL;DR
Firecrawl is scraping optimized for LLMs — it returns clean Markdown/JSON and has a /crawl endpoint that walks a site. ScrapingBee is a general-purpose headless-browser scraping API that returns raw HTML. Firecrawl wins for RAG pipelines; ScrapingBee wins when you want to parse HTML yourself with flexibility.
Pick Firecrawl
Pick Firecrawl when your end use is LLM (RAG, summarization, extract).
Pick ScrapingBee
Pick ScrapingBee when you want raw HTML and your own parsing (Cheerio, BeautifulSoup).
Feature-by-feature comparison
| Feature | 🔥Firecrawl | 🐝ScrapingBee | Winner |
|---|---|---|---|
| Output | Markdown + LLM-ready JSON | Raw HTML + screenshots | Tie |
| Crawl whole site | Native /crawl | Not built-in | A |
| JS rendering | Default | Default | Tie |
| Extract API (LLM-guided) | Yes (extract) | Limited | A |
| Proxy types | Rotating pool | Datacenter + residential | B |
| Screenshot API | Yes | Yes | Tie |
| Google search API | No (use Tavily) | Google search add-on | B |
| Price per 1000 req | ~$2-5 | ~$1-3 | B |
Output
TieFirecrawl
Markdown + LLM-ready JSON
ScrapingBee
Raw HTML + screenshots
Crawl whole site
AFirecrawl
Native /crawl
ScrapingBee
Not built-in
JS rendering
TieFirecrawl
Default
ScrapingBee
Default
Extract API (LLM-guided)
AFirecrawl
Yes (extract)
ScrapingBee
Limited
Proxy types
BFirecrawl
Rotating pool
ScrapingBee
Datacenter + residential
Screenshot API
TieFirecrawl
Yes
ScrapingBee
Yes
Google search API
BFirecrawl
No (use Tavily)
ScrapingBee
Google search add-on
Price per 1000 req
BFirecrawl
~$2-5
ScrapingBee
~$1-3
Best for
Firecrawl
- Crawl whole site: Native /crawl
- Extract API (LLM-guided): Yes (extract)
Best for
ScrapingBee
- Proxy types: Datacenter + residential
- Google search API: Google search add-on
- Price per 1000 req: ~$1-3
Migration path
Both are simple REST APIs. ScrapingBee → Firecrawl: replace the /api/v1/?url=... call with firecrawl.scrape_url(), drop your own HTML parser in favor of Firecrawl's extract schema. Firecrawl → ScrapingBee: add a parser (Cheerio/BS4) on the HTML, reimplement crawl-depth logic yourself with a queue.
Frequently asked questions
What is the main difference between Firecrawl and ScrapingBee?
Firecrawl is scraping optimized for LLMs — it returns clean Markdown/JSON and has a /crawl endpoint that walks a site. ScrapingBee is a general-purpose headless-browser scraping API that returns raw HTML. Firecrawl wins for RAG pipelines; ScrapingBee wins when you want to parse HTML yourself with flexibility. In short: Firecrawl — LLM-ready web scraping API. ScrapingBee — Headless browser scraping API.
When should I pick Firecrawl over ScrapingBee?
Pick Firecrawl when your end use is LLM (RAG, summarization, extract).
When should I pick ScrapingBee over Firecrawl?
Pick ScrapingBee when you want raw HTML and your own parsing (Cheerio, BeautifulSoup).
Can I migrate from one to the other?
Both are simple REST APIs. ScrapingBee → Firecrawl: replace the /api/v1/?url=... call with firecrawl.scrape_url(), drop your own HTML parser in favor of Firecrawl's extract schema. Firecrawl → ScrapingBee: add a parser (Cheerio/BS4) on the HTML, reimplement crawl-depth logic yourself with a queue.
Do Firecrawl and ScrapingBee both work with MCP-compatible AI agents?
Yes. Both have MCP servers installable via MCPizy (mcpizy install firecrawl and mcpizy install scrapingbee). They work identically across Claude Code, Claude Desktop, Cursor, Windsurf, and any other MCP-compatible client. You can install both side by side and route queries in your agent's prompt.
More Scraping & Search comparisons
Firecrawl vs Apify
Firecrawl is the new LLM-era scraping API — hit one URL, get back clean Markdown ready for RAG. Apify is the veteran platform with 2000+ pre-built 'actors' for specific sites (LinkedIn, Amazon, Google Maps, etc.) and more general workflow tooling. Firecrawl wins for 'crawl a site and feed an LLM'; Apify wins for 'scrape LinkedIn profiles at scale'.
Meilisearch vs Algolia
Algolia is the enterprise hosted search — highest polish, best A/B testing, typo tolerance, ranking, analytics. Meilisearch is open-source, self-hostable, and developer-friendly with a free managed Cloud tier. For a fast build with SDKs and enterprise support, Algolia. For open-source / cost control, Meilisearch.
Meilisearch vs Elasticsearch
Meilisearch is a lean, developer-friendly search engine with instant-search and good typo tolerance. Elasticsearch is the heavyweight — fully featured search, analytics, logs, aggregations, and geospatial. For small/medium product search, Meilisearch is faster to adopt; for complex analytics + search + logs, ES.
Install both with MCPizy
Not sure? Run both side by side — swap between them in your AI agent with a single config line.