Best web scraping API in 2026: 11 web scraping tools and AI scrapers compared

Where it wins. Crawl, JavaScript rendering and typed schema extraction happen in a single API call, and robots.txt plus site Terms of Service are respected by default.

What to watch. There is no free plan, so it is priced for teams running real pipelines rather than one-off experiments.

Pick it if. Teams that want one compliance-first pipeline returning LLM-ready data for RAG and agents.

Where it wins. Excellent developer experience, a well-loved open-source project, and markdown output tuned for token efficiency.

What to watch. The headline 1 credit a page is the plain scrape only. Asking for structured JSON adds 4 credits, so a page you want back as typed fields is 5 credits, which turns Standard from $0.83 into $4.15 per 1,000 pages. PDF parsing adds 1 credit a PDF page, a prompt injection check adds 4, zero data retention adds 1, Map is 1 credit a call, Search is 2 per 10 results, and Interact is 2 to 7 credits a browser minute. Credits are charged whenever the request is processed, regardless of what the target returns.

Pick it if. Fast site-to-markdown for LLM workflows, and teams that want the option to self-host.

Where it wins. The largest proxy network in the category (150M+ residential IPs across 195 countries) and hundreds of prebuilt domain scrapers and ready-made datasets.

What to watch. It is a broad platform rather than a single LLM-ready endpoint, so output usually needs cleaning before you can embed it, and the pricing surface is complex.

Pick it if. Enterprise-scale proxy networks and prebuilt datasets for hard, heavily defended targets.

Where it wins. A marketplace of thousands of prebuilt Actors, so common targets are already solved, plus a full automation and scheduling platform.

What to watch. Costs stack in layers: the plan buys a dollar allowance, Actor compute burns it at $0.13 to $0.20 per compute unit, and residential proxies add $7 to $8 per GB on top. Unused allowance expires monthly, and output is generic JSON rather than LLM-ready markdown.

Pick it if. Teams that want a prebuilt scraper for a specific site rather than building one.

Where it wins. Very easy to adopt, dependable rendering, and a Google Search API bundled into every tier.

What to watch. JavaScript rendering is on by default and costs 5 credits, so a Freelance plan is 50,000 rendered pages rather than the 250,000 the credit count suggests. Premium proxy is 10 credits alone or 25 with rendering, and stealth proxy is 75. You also mostly get HTML back, so the cleaning, chunking and structuring work for an LLM is still yours to do.

Pick it if. Simple proxy plus JavaScript rendering behind a clean REST API.

Where it wins. Strong price per request at volume and a very simple drop-in proxy API.

What to watch. The multipliers decide the bill: a flat request is 1 credit, render adds 10, premium adds 10, premium with render is 25, ultra premium with render is 75, and Amazon, SERP and LinkedIn targets are 5, 25 and 30. It is proxy infrastructure first, so an LLM pipeline still needs its own parsing, boilerplate stripping and schema layer.

Pick it if. High-volume proxy rotation at a low cost per request.

Where it wins. Focused on getting through Cloudflare, DataDome and PerimeterX where simpler fetchers fail.

What to watch. The multipliers set the real price, not the headline credit count: a plain fetch is 1 credit, a JavaScript-rendered page is 5, premium proxies are 10, and premium with rendering is 25, which is the ceiling. Residential bandwidth is billed at a flat 25,000 credits per GB, and Browser Sessions add 5 credits a minute on top of bandwidth. Launch at $57 therefore buys about 50,000 rendered pages. You also get HTML back, so the cleaning and structuring work for an LLM is still yours.

Pick it if. Sites behind aggressive anti-bot systems.

Where it wins. Enterprise-grade unblocking, a large global proxy network, and dedicated parsers for major targets, plus a free Custom Parser for your own CSS or XPath rules.

What to watch. The headline result counts are best-case for a single cheap target: Oxylabs own FAQ notes the Micro plan's 98,000 results apply to Amazon, and spreading the same plan across mixed targets works out closer to 16,000 per target. Whole-site crawling means buying a second product.

Pick it if. Enterprises pulling high volumes from hard, well-known targets like major marketplaces.

Where it wins. No vendor bill at all, full control, deep crawling with BFS, DFS and best-first strategies, and output already shaped for RAG ingestion. It is the most popular open-source crawler in the category, with roughly 72,000 GitHub stars.

What to watch. You own the ops: proxy rotation, browser fleet, retries, blocks and upgrades. Free software is not free infrastructure.

Pick it if. Engineering teams happy to run and maintain the infrastructure themselves.

Where it wins. A pre-built Knowledge Graph of more than 10 billion entities you can query instead of crawling, and computer-vision extraction that classifies and structures pages with no per-site rules to write.

What to watch. The first paid tier is $299 a month and credits are consumed fast (a Knowledge Graph record costs 25 credits, a data-center proxy request doubles the cost), so for plain RAG ingestion it is expensive and heavier than you need.

Pick it if. Enterprises that need web-wide entity intelligence and rule-less extraction across many different site layouts.

Where it wins. The open-source library (MIT, 28.4k GitHub stars) is a genuine option rather than a demo, it plugs into OpenAI, Groq, Azure, Gemini or a local Ollama model, and the managed API starts at $20 a month, below our own floor.

What to watch. The managed API bills per credit and the rate depends on the endpoint (extract costs 5 credits, stealth adds 5, a crawl adds 2 on top of per-page scrape cost), so cost per page is harder to predict. Self-hosting means you supply the LLM key and pay model tokens on every page.

Pick it if. Teams that want LLM-driven extraction from a plain-English prompt, or an MIT-licensed Python library they can run themselves.