6 web scraping APIs to evaluate for LLMs in 2026

An LLM application needs more than a successful page request. It needs the right content, a usable output format, source links, and errors it can act on. Evaluate these separately when choosing an extraction API.

This guide compares publicly documented product capabilities, not results from a shared performance benchmark. I build Webclaw; the Webclaw section below describes its API rather than an independent ranking.

What changes when the consumer is an LLM

Output quality: Compare raw HTML, Markdown, and structured output using both token count and retained facts. Shorter text can still omit a price, qualification, or source your application needs.

Access and errors: Test static pages, client-rendered pages, and any protected targets in your actual workload. A successful HTTP status is insufficient if the body is a challenge page or incomplete content.

Latency and cost: Measure the complete request, including rendering, retries, and post-processing. Record cold and cached runs separately, and calculate cost per usable result.

Integration: Check the SDK, MCP tools, request options, and response fields your application will use. A supported endpoint does not establish compatibility with every option.

The options

Jina Reader

Jina Reader provides a URL-to-content workflow using the r.jina.ai prefix. Its documented options include output formats, selectors, browser viewport settings, page readiness, cache controls, and custom JavaScript before extraction.

Evaluate it for a reader workflow where you want extracted content through a small HTTP integration. Validate your selected rendering and output options on the target pages.

Firecrawl

Firecrawl documents scraping, crawling, search, and structured extraction, with SDK and MCP integrations. It is an option to evaluate when those interfaces fit your application's existing tools.

Protected-page success varies by target and configuration. This article does not establish a comparative success rate or infer the provider's private retrieval implementation.

ScrapingBee

ScrapingBee provides an API with JavaScript rendering and extraction options. Its current product documentation also describes AI-oriented extraction; evaluate the output mode you need rather than assuming every request returns only HTML.

Browser execution can add latency. Measure the pages, rendering options, and waits your application actually uses.

Scrapfly

Scrapfly exposes configurable retrieval and rendering options. Compare its output, latency, and target coverage using the same acceptance criteria as the other providers.

Choose request options based on the content required, and include their credit cost in the comparison.

Apify

Apify is a platform for running Actors: programs with their own input, execution, and output contracts. Actors can provide site-specific workflows or more general extraction.

Evaluate it when a selected Actor or custom program matches your workflow. Check that Actor's maintenance, pricing, and output schema; those details vary across the catalog.

Webclaw

Webclaw offers a Scrape API, crawling, search, structured extraction, and an MCP server. It can render JavaScript when required. Access to protected pages remains best effort and target-dependent.

The scrape output choices include:

• markdown: Markdown content.
• llm: text with reduced markup, repeated links, and boilerplate; validate retained facts against the source.
• json: structured page content and metadata.
• text: plain text.
• extract: schema- or prompt-directed extraction, configured with nested extract.schema and/or extract.prompt.

Use the documented formats array for hosted API requests. MCP tools have their own argument schema, so follow the MCP reference rather than copying HTTP fields unchanged.

# CLI
webclaw https://example.com --format llm

# API
curl -X POST https://api.webclaw.io/v1/scrape \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"url": "https://example.com", "formats": ["llm"]}'

{
  "mcpServers": {
    "webclaw": {
      "command": "npx",
      "args": ["-y", "@webclaw/mcp"]
    }
  }
}

Compare using your own workload

Use the same URLs, expected facts, options, and measurement windows for each provider. Keep failed requests in the results instead of benchmarking only successes.

Migrating from Firecrawl

Webclaw provides compatibility endpoints for Firecrawl v2-style scrape, crawl, and search requests. See the API compatibility reference for supported fields and limitations. Validate every option and response field your application depends on before switching providers.

Frequently asked questions

What's the best scraping API for a RAG pipeline?

The answer depends on the corpus. Compare retained content, source evidence, access success, latency, and cost. Markdown output alone does not prove that extraction preserves the facts your retrieval system needs.

Can these APIs work with AI agents?

An agent can call an HTTP API through a tool integration. Several providers also publish MCP servers or framework integrations. Webclaw's MCP documentation lists its supported tools and arguments.

Do these tools handle JavaScript-rendered pages?

The products above document rendering or browser-based workflows, but behavior and request options differ. Test the specific client-loaded content your application needs; rendering support is not a guarantee that every target will work.

How much can Webclaw reduce tokens?

In the 2026-04-17 benchmark of Webclaw v0.3.18, three runs across 18 sites using cl100k_base showed 92.5% mean token reduction. The output retained 76 of 90 curated visible facts. This historical result is not a guarantee for other pages or current releases.