Top 10 web scraping APIs for AI in 2026

AI applications run on data, and most of that data lives on the web. The problem is that the web wasn't designed for machines. JavaScript rendering, bot detection, session requirements, and constantly changing page structures make reliable data collection genuinely hard engineering work.

Web scraping APIs take that complexity off your plate. They handle headless browsers, proxy rotation, CAPTCHA solving, and content parsing so you can focus on building.

The challenge is that the market has exploded, and not all of them are worth your time, especially for AI use cases, where output format and extraction accuracy matter as much as raw uptime.

We put together this comparison after thorough research across ten of the most-discussed scraping APIs in the AI developer community. We looked at output quality for LLM consumption, structured data extraction, anti-bot bypass, browser interaction capability, and real-world pricing.

Here's what we found.

Quick comparison

1. Spidra

Spidra is an AI-native web scraping platform built from scratch around the idea that you should be able to describe what you want and get it back as structured data without writing selectors, managing infrastructure, or fighting anti-bot systems yourself.

What separates Spidra from everything else on this list is its browser action pipeline. Most scraping APIs fetch a static snapshot of a page. Spidra lets you interact with the page before scraping it: click cookie banners, type into search fields, scroll lazy-loaded content, and loop through every element with the forEach action, including automatic pagination across multiple pages.

Key features

• Prompt-based AI extraction — describe what you want in plain English, get back clean JSON
• JSON schema support — lock down the exact shape of your output; nullable required fields always appear in results
• Browser action pipeline — click, type, scroll, check, wait, and the unique forEach loop
• forEach — three modes: inline (reads elements directly), navigate (follows each element as a link), click (expands each element); supports maxItems, per-item itemPrompt, nested sub-actions, and automatic pagination
• Batch scraping — up to 50 URLs processed in parallel per request
• Full-site crawling — AI-guided link discovery with per-page extraction instructions
• Built-in CAPTCHA solving and residential proxy rotation across 50 countries, billed against bandwidth (not credits)
• Authenticated scraping — pass session cookies for login-protected pages
• Output delivery — Slack, Discord, Email, Telegram, Webhook; JSON, CSV, and screenshot export
• SDKs: JavaScript, Python, Node.js, Go, Rust, Java, Elixir

import requests

response = requests.post(
    "https://api.spidra.io/api/scrape",
    headers={"x-api-key": "YOUR_API_KEY"},
    json={
        "urls": [{
            "url": "https://store.example.com/products",
            "actions": [
                {"type": "click", "value": "Accept cookies button"},
                {
                    "type": "forEach",
                    "observe": "Find all product cards",
                    "mode": "navigate",
                    "maxItems": 20,
                    "itemPrompt": "Extract name, price, and availability as JSON",
                    "pagination": {"nextSelector": "li.next > a", "maxPages": 3}
                }
            ]
        }],
        "output": "json"
    }
)

Limitations

• MCP server not yet available (on the roadmap)
• Newer platform — community and third-party integrations are still growing
• Maximum 3 URLs per scrape request; use the batch endpoint for larger volumes

Pricing

• Free: 300 credits, 50 MB bandwidth — no credit card required
• Starter: $19/month — 5,000 credits, 500 MB bandwidth
• Builder: $79/month — 25,000 credits, 2 GB bandwidth, advanced stealth
• Pro: $249/month — 125,000 credits, 5 GB bandwidth, priority support
• Enterprise: Custom — dedicated infrastructure, SLAs, white-label API

Best for: AI data pipelines, lead generation, price monitoring, and any workflow that requires interacting with a page before scraping it. The forEach loop is genuinely unique, and no other tool on this list handles paginated element-level scraping natively in a single API call.

Get started for free

2. Firecrawl

Firecrawl markets itself as the web context API for AI agents, and with over 121,000 GitHub stars and more than a million signups, it's the tool with the most developer mindshare in this space. It covers search, scraping, crawling, and now browser interaction through a single API, with an open-source core that's auditable and self-hostable.

Key features

• Scrape endpoint — returns Markdown, HTML, screenshots, metadata, or extracted JSON matching a schema; handles JavaScript rendering automatically
• Crawl endpoint — follows links across an entire site or section with configurable depth, page limits, and path filters; respects robots.txt
• Search endpoint — returns search results with full-page Markdown already included in one call
• Interact — click, scroll, type, navigate, and wait on any page before extracting; billed at 2 credits per browser minute
• Schema-based extraction — pass a JSON or Zod schema, get back structured data with no post-processing
• Media parsing — handles PDFs and DOCX alongside standard web pages
• Caching layer — configurable cache behavior to reduce redundant fetches
• Official MCP server — works with Cursor, Claude, Windsurf, and other MCP-compatible tools; over 400,000 MCP server installs reported
• Framework integrations: LangChain, LlamaIndex, CrewAI, AutoGen, Agno, FlowiseAI
• SDKs: Python, Node.js, Go, Rust, Java, Elixir

from firecrawl import Firecrawl

app = Firecrawl(api_key="fc-YOUR_API_KEY")

result = app.scrape(
    "https://docs.example.com/guide",
    formats=["markdown"],
    extract={
        "schema": {
            "type": "object",
            "properties": {
                "title": {"type": "string"},
                "summary": {"type": "string"}
            }
        }
    }
)
print(result["markdown"])

Limitations

• Interact actions cost 2 credits per browser minute — factor this into cost estimates for automation-heavy workflows
• No authenticated session handling via cookies
• No parallel batch endpoint for high-volume URL lists

Pricing

• Free: 1,000 credits/month, no card required
• Hobby: $16/month — 5,000 credits, 5 concurrent requests
• Standard: $83/month — 100,000 credits, 50 concurrent requests (most popular)
• Growth: $333/month — 500,000 credits, 100 concurrent requests
• Scale: $599/month — 1,000,000 credits, 150 concurrent requests
• Credits don't roll over month-to-month (auto-recharge packs are the exception)

Best for: Developers building AI agents and RAG pipelines, especially those already using LangChain or LlamaIndex. The open-source core, broad SDK support, and MCP adoption make it the default starting point for most AI developers reaching for a scraping tool.

3. Spider.cloud

Spider.cloud is a web data API built in Rust, focused on speed and cost efficiency. The team claims throughput of 100,000 pages per second, and the pricing model — charged per bandwidth plus compute rather than a subscription — means you only pay for what you actually use.

Key features

• Multiple output formats — Markdown, HTML, plain text, JSON, JSONL, CSV, XML, and PDF
• Smart rendering mode — auto-detects whether each page needs a headless browser and switches accordingly; reduces cost compared to forcing browser rendering on every request
• AI extraction — vision models read the rendered page and return structured JSON from a plain-English prompt
• Browser Cloud — full headless browser sessions with anti-detection, automatic CAPTCHA solving, and proxy rotation; handles Cloudflare and other protections
• Web Search API — returns real search results with full-page Markdown already scraped, in under 3 seconds
• Streaming results — data starts coming back as soon as the first pages complete, rather than waiting for the full batch
• 200M+ rotating proxies across 199 countries
• MCP server available
• Open-source core — the underlying spider-rs crawler is available on GitHub
• Framework integrations: LangChain, LlamaIndex, CrewAI, AutoGen, Agno, Dify
• SDKs: Python, JavaScript, Rust, Go

import spider

client = spider.Spider(api_key="YOUR_API_KEY")

result = client.scrape_url(
    "https://example.com",
    params={
        "return_format": "markdown",
        "proxy_enabled": True,
        "ai_query": "Get all product names and prices"
    }
)
print(result[0]["content"])

Limitations

• No authenticated session handling via cookies
• Pricing based on bandwidth + compute can be hard to predict before you understand your traffic patterns; use the cost calculator on their site
• Community is smaller than Firecrawl's

Pricing

• Pay-per-use: bandwidth charged at $1/GB plus compute at $0.001/minute
• Most pages cost well under $0.001 each
• 2,500 free credits on signup, no card required; credits never expire
• Failed requests are not billed

Best for: High-volume crawling and data pipelines where throughput and cost-per-page matter more than anything else. The pay-per-use model is particularly attractive for variable or bursty workloads.

4. Context.dev

Context.dev combines web scraping with brand intelligence in a single API. The scraping endpoints produce Markdown and structured data, while the brand endpoints return logos, color palettes, social profiles, industry codes, and company descriptions for any domain name. No other tool on this list offers both from the same place.

Key features

• Markdown API — scrapes any URL and returns clean, LLM-ready output; strips navigation, ads, and other boilerplate
• HTML API — full headless browser rendering for JavaScript-heavy pages
• Sitemap API — discovers and parses all page URLs on a domain before you start crawling
• Images API — extracts all images from a URL with source, alt text, and dimensions
• Screenshot API — viewport or full-page screenshots via CDN
• AI Query — define data points in plain English; the API returns structured JSON matching your description
• AI Product / AI Products — extracts structured product data from any e-commerce URL; natively supports Amazon, Etsy, TikTok Shop, and generic product pages
• Brand Retrieve — pass a domain and get logos, colors, description, address, industries, and social links; also searchable by email, ticker, or company name
• Logo Link — embed any company logo as a plain <img> tag pointing to their CDN
• Fonts, Colors, Styleguide APIs — dedicated endpoints for brand design data
• Official MCP server
• SDKs: TypeScript, Python, Ruby, Go

import ContextDev from 'context.dev';

const client = new ContextDev({ apiKey: process.env.CONTEXT_DEV_API_KEY });

const { markdown } = await client.brand.markdown({ url: 'https://example.com/about' });
const brand = await client.brand.retrieve({ domain: 'example.com' });
// brand: { logos, colors, description, address, industries, socials }

Limitations

• No browser action pipeline — cannot click, type, scroll, or interact before scraping
• No authenticated session handling
• No parallel batch endpoint for high-volume URL lists
• Higher entry price compared to most competitors

Pricing

• Free: 500 credits — no card required
• Starter: $49/month — 30,000 credits
• Pro: $149/month — 200,000 credits
• Scale: $949/month — 2,500,000 credits

Best for: AI applications that need both scraped web content and structured company metadata — enrichment pipelines, onboarding personalization, and any product where brand context matters alongside page content.

5. Jina AI Reader

Jina AI Reader is the most minimal approach on this list: prepend any URL with r.jina.ai/ and you get back clean Markdown. No SDK installation, no configuration, no API key needed for basic usage. It's the fastest path from URL to LLM-ready text.

Key features

• Zero-config Markdown conversion — just prepend the URL
• Strips navigation, advertising, and HTML clutter automatically
• CSS selector targeting for focused extraction on specific page sections
• Shadow DOM extraction and iframe content support
• Screenshot and full-page capture modes
• EU-compliant endpoint
• Official MCP server
• SDKs: Python, JavaScript

# No setup needed. Works immediately.
curl https://r.jina.ai/https://example.com

Limitations

• Single-page only — no site crawling or link following
• Returns Markdown only — no structured JSON extraction
• No anti-bot bypass for protected sites
• No browser interaction of any kind

Pricing

• Free: 10 million tokens on signup, 100 requests per minute
• Paid: approximately $0.02 per million tokens

Best for: Developers who need to pull a page's content for an LLM prompt quickly and cleanly. The zero-setup approach makes it ideal for scripts, notebooks, and prototypes where you don't want to configure anything.

6. Crawl4AI

Crawl4AI is an open-source Python library purpose-built for feeding LLMs and RAG pipelines. The appeal is straightforward: no per-request pricing, full control over the stack, and deep hooks for customizing exactly how content gets cleaned and chunked.

Key features

• Markdown output optimized for RAG — uses BM25-based content filtering to prioritize relevant content
• LLM-powered extraction using any model you choose (OpenAI, local, or open-source)
• Full-site crawling with depth control, link filtering, and parallel processing
• Session reuse and crash recovery for large crawls
• Stealth mode with configurable browser fingerprinting
• Async-first architecture for high-concurrency workloads
• Community-maintained MCP servers
• SDKs: Python only

import asyncio
from crawl4ai import AsyncWebCrawler

async def main():
    async with AsyncWebCrawler(verbose=True) as crawler:
        result = await crawler.arun(url="https://docs.example.com")
        print(result.markdown)

asyncio.run(main())

Limitations

• Self-hosted setup requires you to manage your own infrastructure and dependencies
• Python only — no JavaScript, TypeScript, or Go SDK
• Anti-bot bypass is not at the level of commercial providers
• Steeper learning curve than any hosted API solution

Pricing

• Open-source: completely free, self-hosted
• Managed cloud: $1 per 1,000 pages
• Pro: $99/month — advanced proxies, unlimited concurrency

Best for: Python teams who want full control over their scraping pipeline without paying per-request fees. Particularly strong for RAG pipelines with large crawl volumes where the cost savings at scale are significant.

7. Apify

Apify is less of a scraping API and more of a cloud automation platform. The core concept is Actors — serverless scraping programs that run on Apify's infrastructure. You can build your own or pull from the Apify Store, which has over 10,000 pre-built scrapers for specific platforms. It's been rated the #1 web scraping software on Capterra and is trusted by companies including Intercom, which uses it to feed data into its AI products.

Key features

• 10,000+ Actors in the Apify Store for specific targets: Google Maps, Amazon, LinkedIn, Instagram, YouTube, TikTok, GitHub, Indeed, Zillow, and hundreds more
• Website Content Crawler — crawls entire sites and produces Markdown output optimized for LLM training and RAG pipelines
• Crawlee SDK — open-source browser automation library for building custom Actors in JavaScript or Python
• Multiple rendering backends — Playwright for JavaScript-heavy pages, Cheerio for fast HTTP scraping
• Scheduling, monitoring, and dataset storage — built into the platform
• Export formats — JSON, CSV, Excel, XML, RSS; direct push to Snowflake, BigQuery, Redshift
• Official MCP server — AI agents can discover and use Actors dynamically
• Integrations: LangChain, Hugging Face, Zapier, Make, Airbyte, Keboola
• SOC 2 Type II, GDPR, CCPA compliant
• SDKs: JavaScript, Python

import { PlaywrightCrawler } from 'crawlee';

const crawler = new PlaywrightCrawler({
    async requestHandler({ page, enqueueLinks }) {
        const title = await page.title();
        console.log(`Scraped: ${title}`);
        await enqueueLinks();
    }
});

await crawler.run(['https://example.com']);

Limitations

• The Actor model and platform concepts have a real learning curve; users commonly report that understanding compute units and Actor-specific pricing takes time
• Costs can compound at scale — compute, proxy, and storage fees stack
• Actor quality varies; some community-built Actors are not well maintained
• Not specifically optimized for LLM Markdown output the way newer tools are

Pricing

• Free: $5/month in platform credits, no card required
• Starter: $29/month — more credits, chat support
• Scale: $199/month — priority support
• Business: $999/month — dedicated account manager
• Pay-as-you-go usage billed on top of plan at $0.20–$0.30 per compute unit depending on tier
• Some Actors in the Store have additional rental fees

Best for: Teams that need ready-made scrapers for specific platforms — particularly high-value targets like Google Maps, LinkedIn, or Amazon — or complex automation workflows that go beyond simple page extraction.

8. Diffbot

Diffbot takes a different approach than anything else on this list. Rather than returning raw content for you to process, it uses computer vision and machine learning to automatically classify pages by type and extract structured data without any selectors or prompts. It also maintains one of the largest continuously updated Knowledge Graphs on the web.

Key features

• Automatic page classification — detects whether a URL is an article, product, discussion, image, video, or other type; applies the appropriate extraction model automatically
• ML-powered extraction — returns structured fields specific to the page type (articles get title, author, date, body, tags; products get name, price, features, availability)
• Knowledge Graph — over 264 million organizations and 1.6 billion articles, continuously updated via automated crawls; queryable for entity relationships, industry classification, funding rounds, and more
• NLP layer — entity recognition, relationship extraction, and sentiment analysis built into article responses
• Crawlbot — automated full-site crawling that feeds results directly into Diffbot's extraction pipeline
• SDKs: Python, JavaScript

import diffbot

client = diffbot.DiffbotClient(token="YOUR_TOKEN")

# Automatic classification — no page type configuration needed
result = client.article("https://techcrunch.com/2026/01/01/example-article")
# Returns: title, author, date, body, tags, entities, sentiment, links

Limitations

• The $299/month minimum is a significant barrier for small teams or individual developers
• Output is structured JSON, not Markdown — not optimized for direct LLM context window injection
• No integrations with LangChain, LlamaIndex, or other AI frameworks
• No MCP server
• No browser action pipeline

Pricing

• 14-day free trial with full API access
• Startup: $299/month
• Plus: $899/month
• Custom enterprise pricing available

Best for: Enterprise teams that need automatic structured extraction at scale — particularly where automatic page classification, entity enrichment, or Knowledge Graph querying provides value that offsets the cost.

9. ScrapingBee

ScrapingBee is a straightforward scraping API that wraps headless Chrome, proxy rotation, and CAPTCHA handling behind a single endpoint. Founded in France in 2019, it grew to over 2,500 customers bootstrapped with a small team, serving companies including SAP, Zapier, Deloitte, and Zillow. It was acquired in mid-2025 while keeping the brand and leadership independent.

Key features

• JavaScript rendering via headless Chrome — handles React, Angular, Vue, and other SPAs
• Rotating proxy pool with geolocation targeting
• AI extraction via ai_query parameter — plain English description of what to pull
• Google Search API and structured SERP data
• Custom JavaScript execution on pages before capture
• Output in HTML, Markdown, JSON, or plain text
• Screenshot capture (viewport and full-page)
• CLI tool for batch processing, crawling, and scheduled cron jobs (launched 2025–2026)
• SDKs: Python, JavaScript

from scrapingbee import ScrapingBeeClient

client = ScrapingBeeClient(api_key="YOUR_API_KEY")

response = client.get(
    "https://example.com/product",
    params={
        "render_js": True,
        "json_response": True,
        "ai_query": "Extract the product name and price"
    }
)

Limitations

• JavaScript rendering is enabled by default — every request costs 5 credits unless you explicitly disable it with render_js=false, which catches many users off guard
• Premium proxy and stealth options push per-request costs to 10–75 credits; the published plan sizes assume basic requests
• JS rendering and geolocation targeting are unavailable on the Freelance ($49) and Startup ($99) plans — you must jump to Business ($249) to access them
• No full-site crawling or link-following (though the CLI adds some crawling capability)
• No MCP server

Pricing

• Free trial: 1,000 API credits, no card required
• Freelance: $49/month — credits undisclosed but approximately 150K at basic rates
• Startup: $99/month — approximately 1M basic credits
• Business: $249/month — approximately 3M basic credits, JS rendering and geotargeting unlocked
• Business+: $599+/month for higher volume

Best for: Developers who want a clean, simple API for scraping individual pages and are comfortable reading HTML output. Well-regarded for reliability and responsive support, with caveats around credit consumption when JS rendering is involved.

10. ZenRows

ZenRows has carved out a position as the anti-bot specialist in the scraping API market. Its entire stack — proxies, browser fingerprinting, CAPTCHA solving, and request handling — is engineered to consistently get through the toughest bot detection systems.

Key features

• Universal Scraper API — single endpoint covering static, JavaScript-rendered, and bot-protected pages
• Autoparse — converts page content to structured JSON automatically without selectors
• Markdown output — LLM-ready output mode that reduces token count while preserving page meaning
• Scraping Browser — cloud-hosted Playwright/Puppeteer sessions with anti-detection built in
• Residential proxy network with automatic rotation and geo-targeting
• Handles Cloudflare, DataDome, PerimeterX and other sophisticated bot protection systems
• Shared balance — a single credit balance works across all ZenRows products (Scraper API, Browser, Proxies)
• SDKs: Python, JavaScript

import requests

response = requests.get(
    "https://api.zenrows.com/v1/",
    params={
        "apikey": "YOUR_API_KEY",
        "url": "https://protected-site.com",
        "antibot": True,
        "markdown_response": True
    }
)
print(response.text)

Limitations

• Credit multipliers are the biggest gotcha: enabling JavaScript rendering multiplies cost by 5x, and premium proxies can push it to 25x; some protected domains trigger the 25x multiplier automatically. A Developer plan showing 250,000 basic results may yield only 10,000 results on heavily protected sites
• No full-site crawling or link following
• No browser action pipeline for interacting with pages
• No MCP server
• Entry price of ~$70/month with no permanent free tier is a common complaint from smaller teams

Pricing

• Free trial: 14-day trial with $1 usage allowance across all products
• Developer: approximately $70/month — 250K basic results, 10K protected results, 12.73 GB bandwidth
• Startup: approximately $129/month — 1M basic results, 40K protected results, 24.76 GB bandwidth
• Business: approximately $299/month — 3M basic results, 120K protected results, 60 GB bandwidth
• Annual billing discounts approximately 10%

Best for: Scraping campaigns where the target sites use aggressive bot detection and other tools consistently fail. If you know your targets and have predictable volume, ZenRows delivers strong reliability; if your workload mixes protected and unprotected sites unpredictably, the multiplier system can create budget surprises.

Bottom line

Spidra earns the top spot because it's the only tool that genuinely covers the full scraping stack in a single platform, from basic fetch-and-extract to multi-step browser automation with forEach loops, pagination, per-element AI extraction, batch processing, full-site crawling, and built-in anti-bot bypass without credit multipliers. That's a combination no other tool here offers.

That said, every tool on this list exists because it solves something well. Firecrawl has the most mature ecosystem for AI developers. Crawl4AI is the right call for teams that want to own their infrastructure. Apify is unmatched for platform-specific pre-built scrapers. Context.dev is the only option when brand data and web scraping belong in the same pipeline. And ZenRows remains the go-to when anti-bot reliability is the single most important factor.

The best choice depends on your stack, your volume, and what your target sites actually require.

Try Spidra free

FAQ

What is a web scraping API?

A web scraping API is a hosted service that extracts content from websites on your behalf. You send a URL and get back the page content in a format your application can use — HTML, Markdown, JSON, or screenshots — without managing browsers, proxies, or anti-bot handling yourself. For AI applications, the key capability is producing clean, structured output that fits neatly into LLM prompts or vector databases.

What makes Spidra different from other scraping APIs?

Most scraping APIs retrieve a page and hand you the content. Spidra lets you interact with the page first through a browser action pipeline — dismissing cookie banners, typing into forms, scrolling, and looping through every matching element with forEach.

This is particularly valuable for modern JavaScript-heavy applications where the data you want only appears after user interaction. It's also one of the few tools that doesn't charge a credit multiplier when you enable anti-bot bypass.

Do web scraping APIs work on Cloudflare-protected sites?

It varies significantly by tool. Spidra, Spider.cloud, ZenRows, and Context.dev include anti-bot bypass by default. Firecrawl has an enhanced mode that handles many protected sites. ScrapingBee and Apify offer protection bypass as add-ons or on higher-tier plans. Jina Reader and Crawl4AI have limited or no anti-bot capability. At meaningful scale, a significant portion of sites you'll want to scrape will have some form of bot detection.

What's the best scraping API for RAG pipelines?

RAG pipelines typically need clean Markdown output, site crawling to discover all relevant pages, and some form of metadata. Firecrawl and Spidra both handle this well. Firecrawl's recursive crawl is more mature; Spidra's crawl endpoint accepts a transformInstruction describing what to extract from each page. For teams wanting full control with no per-page fees, Crawl4AI is the strongest open-source option.

How should I think about scraping API pricing?

Most tools use credit-based models, but the multipliers vary wildly. A plan advertised at 250,000 credits can mean very different things depending on how many credits each request actually consumes. Always check the credit cost for the features you'll actually use — JavaScript rendering, anti-bot bypass, and premium proxies typically multiply cost by 5–25x on most platforms.

Spidra and Spider.cloud are notable exceptions: Spidra bills proxy usage separately against bandwidth rather than credits, and Spider.cloud uses straight bandwidth + compute with no multiplier system.