MarkUDown vs Firecrawl vs Tavily: Which Web Scraping API is Right for You?

TL;DR

Background

As AI applications increasingly rely on fresh, real-world web data, the tooling for web data extraction has exploded. Three APIs have emerged as the most widely used: Firecrawl (great crawling primitives, popular in the LangChain ecosystem), Tavily (purpose-built for AI search and RAG retrieval), and MarkUDown (built by Scrape Technology with a focus on anti-bot bypassing and structured extraction).

MarkUDown's Core Differentiator: 3-Layer Extraction

Most scraping APIs use a single extraction strategy. MarkUDown uses a 3-layer fallback cascade that automatically escalates when a simpler approach fails:

In our tests, MarkUDown successfully extracted content from 94% of protected pages that Firecrawl failed on.

Speed Benchmark

Median response times across 5 runs per test. Measurements include network latency from São Paulo, Brazil to each provider's API.

Full Feature Comparison

AI Data Extraction

All three support some form of AI-powered extraction, but the implementations differ significantly.

MarkUDown — Schema-based with multi-LLM

Define your exact output schema. MarkUDown scrapes the page, then sends the content to Gemini Flash or GPT-4o mini with your schema.

{
  "url": "https://store.example.com/product/x",
  "extract_query": "Product name, price, availability",
  "schema": [
    { "name": "product_name", "type": "String", "active": true },
    { "name": "price", "type": "Number", "active": true },
    { "name": "in_stock", "type": "Boolean", "active": true }
  ],
  "extraction_scope": "single_page"
}

Firecrawl — JSON schema via LLM extract

Pass a JSON Schema or Zod schema and get structured data back. Well-documented and integrates with LangChain's document loaders.

Tavily — Not supported

Tavily is a search API. It returns snippets and content from search results but does not support structured extraction from arbitrary URLs.

Deep Research

The /api/deep-research endpoint runs a Google search, scrapes the top N result pages, and synthesizes everything into a structured research report via LLM.

Tavily's research endpoint is search-focused — it retrieves snippets but does not scrape and synthesize full page content. Firecrawl has no comparable endpoint.

MCP (AI Agent Integration)

All three now ship an MCP server. MarkUDown's MCP has two variants: cloud (npm package) and self-hosted (direct Redis/BullMQ — no extra HTTP hop). The self-hosted variant is unique.

# Cloud MCP — zero setup
npx markudown-mcp

# Claude Desktop config
{
  "mcpServers": {
    "markudown": {
      "command": "npx",
      "args": ["markudown-mcp"],
      "env": { "MARKUDOWN_API_KEY": "your-key" }
    }
  }
}

Pricing Comparison

Pricing is approximate and subject to change. Check each provider's site for current plans.

When to Choose Each

Conclusion

Tavily wins for pure AI search and RAG. It's the fastest and simplest for that use case.

Firecrawl is the safe, well-documented choice for crawling public sites and feeding LLM pipelines.

MarkUDown is the right choice when you need to reliably extract data from any page — including protected ones — and want AI extraction, deep research synthesis, change detection, and a self-hosted option all in one API.