If you're building AI applications, you already know the pain: LLMs need clean, structured web data and getting it reliably is harder than it looks. Between JavaScript-rendered pages, anti-bot protections, and messy HTML, turning a URL into something an AI model can actually use is a real engineering challenge.
Web scraping APIs solve this by handling the heavy lifting, headless browsers, proxy rotation, content extraction, so you can focus on building your product. But not all scraping APIs are built for AI. Some were designed for traditional data extraction and have bolted on LLM features as an afterthought. Others were built from the ground up with AI pipelines in mind. And if you're deciding whether a hosted API is even the right tier, our guide to what a web scraper is covers the full landscape from browser extensions to managed services.
We've tested and compared the top 11 web scraping APIs available today, evaluating them on what matters most for AI use cases: Markdown output quality, structured data extraction, anti-bot bypass, MCP support, and price per page. Here's our ranking.
Why Context.dev Ranks First for AI Web Scraping
Context.dev is our top web scraping API for AI because one platform combines clean Markdown, schema-based extraction, anti-bot handling, brand intelligence, and an MCP server. Firecrawl remains a strong choice for teams invested in its crawling ecosystem, while specialized providers can be better for proxy-heavy enterprise collection or self-hosted workflows.
Quick Comparison
| Tool | Best For | Anti-Bot | AI Extraction | Brand Data | MCP Server | SDKs | Starting Price |
|---|---|---|---|---|---|---|---|
| Context.dev | AI agents needing structured JSON | Built in | Extract, Product, Products | Yes (core) | Yes | TS, Python, Ruby, Go, PHP | $25/mo |
| Firecrawl | RAG pipelines and recursive crawling | Add-on | Schema-based | No | Yes | Python, JS, Go, Rust, Ruby | $16/mo |
| Spider.cloud | High-volume crawling | Built-in | Vision-based | No | Yes | Python, JS, Rust | ~$0.48/1K pages |
| Jina Reader | Quick page-to-Markdown prototyping | None | No | No | Yes | Python, JS | Free |
| Crawl4AI | Self-hosted RAG pipelines | Limited | LLM-based | No | Community | Python | Free (OSS) |
| Apify | Pre-built scrapers and automation | Add-on | Actor-based | No | Yes | JS, Python | $19/mo |
| ScrapingBee | Simple API-based scraping | Add-on | AI extraction | No | Yes | Python, JS | $49/mo |
| Oxylabs | Large-scale proxy infra | Built-in | OxyCopilot (add-on) | No | No | Python, Go | $49/mo |
| Zyte | Enterprise unblocking | Built-in (tiered) | Built-in | No | No | Python | $0.06/1K responses |
| ZenRows | Protected-site scraping | Built-in | Autoparse | No | No | Python, JS | $69/mo |
| Bright Data | Enterprise proxy infra | Built-in (98%+) | Basic | No | No | Python, JS | $1.50/1K results |
| Diffbot (also considered) | Enterprise knowledge graphs | N/A | ML (core) | Partial | No | Python, JS | $299/mo |
1. Context.dev
Context.dev is a web scraping and brand intelligence API purpose-built for AI applications. Its differentiated pitch is a single unified API that returns clean JSON or Markdown and connects directly to LLM workflows and AI clients through its MCP server. While most scraping tools focus on raw HTML extraction, Context.dev provides a full suite of endpoints designed for feeding clean data into LLMs, RAG pipelines, and AI agents.
Web Scraping Endpoints
Markdown API, Scrape a URL as GitHub Flavored Markdown. Set useMainContentOnly: true to remove surrounding page chrome; it defaults to false. You can also control whether links and images are preserved.
const response = await fetch('https://api.context.dev/v1/web/scrape/markdown?url=https://example.com', {
headers: { Authorization: 'Bearer YOUR_API_KEY' },
});
const { markdown } = await response.json();
// Clean, LLM-ready markdown, no post-processing neededHTML API, Full headless browser rendering for JavaScript-heavy pages. Returns the complete DOM after JS execution, what a real user sees, not the empty <div id="root"></div> shell.
Images API, Extract all images from any webpage with source URLs, alt text, and dimensions. Useful for multimodal AI pipelines.
Sitemap API, Discover and parse sitemaps to get a complete URL inventory for any domain. Scrape only the pages you need instead of blindly crawling.
Screenshot API, Viewport or full-page screenshots served from a CDN for visual AI use cases like design analysis and multimodal document understanding.
Structured Extraction
Context.dev's Extract API crawls from a URL and returns data matching a caller-supplied JSON Schema, without CSS selectors or brittle parsing rules.
The Product API extracts structured product data from an e-commerce URL, while Products discovers and extracts products across a domain.
// Extract structured data matching your JSON Schema
const result = await client.web.extract({
url: 'https://example.com',
schema: {
type: 'object',
properties: { ceo_name: { type: 'string' } },
required: ['ceo_name'],
},
});
// Extract product data from any e-commerce URL
const product = await client.ai.extractProduct({ url: 'https://amazon.com/dp/B0...' });
// Returns: name, description, features, images, tags, price, currency, billing_frequencyBrand Intelligence APIs
No other scraping API handles brand data natively. Context.dev has dedicated endpoints for extracting structured brand information:
Brand Retrieve, Pass any domain and get a complete brand profile: logos, colors, description, address, industries, and social links. Also available via email, stock ticker, or company name lookup.
Logo Link, Embed any company logo with a single img URL. Logo Link delivers square logos instantly from a global CDN, no API calls, no storage, no setup. Just an <img> tag pointing to logos.context.dev.
Fonts API, Extract fonts used on any website, ranked by usage frequency.
const brand = await client.brand.retrieve({ type: 'by_domain', domain: 'stripe.com' });
// Returns: logos, colors, description, address, industries, social links
// Or look up by email, ticker, or company name
const byEmail = await client.brand.retrieve({ type: 'by_email', email: 'contact@stripe.com' });
const byTicker = await client.brand.retrieve({ type: 'by_ticker', ticker: 'AAPL' });
const byName = await client.brand.retrieve({ type: 'by_name', name: 'Stripe' });Anti-Bot Bypass
Anti-bot handling is built into web requests, with proxy escalation and browser rendering managed by Context.dev. It does not require a separate per-request feature flag or credit multiplier.
Pricing
- Free: 1,000 credits/month at 30 req/min, plus 10K one-time Logo Link requests
- Developer: $25/month ($250/year) for 10,000 monthly credits, 1,000 brand retrievals, 100K monthly Logo Link requests, 60 req/min, $15/10K overage
- Pro: $149/month ($1,490/year) for 200,000 credits, 20,000 brand retrievals, 2.5M Logo Link requests, 300 req/min, $9/10K overage
- Scale: $499/month ($4,990/year) for 1,000,000 credits, 100,000 brand retrievals, 10M Logo Link requests, 700 req/min, $7/10K overage
- Enterprise: Custom pricing, limits, security, and procurement support
- All web scraping and brand API endpoints included at every tier
- SDKs: TypeScript, Python, Ruby, Go, PHP
Best for: AI agents, RAG pipelines, LLM-powered applications, brand data enrichment, and teams that want web scraping and company data from a single API.
2. Firecrawl
Firecrawl deserves credit as the tool that popularized the "web scraping for LLMs" category. It has the strongest developer mindshare in the AI scraping space, excellent documentation, and deep integrations with LangChain, LlamaIndex, and CrewAI that make it the default choice for many AI developers.
Key Features
- Markdown extraction with content cleaning and noise removal
- Full-site crawling that follows links and respects robots.txt, one of the best recursive crawlers available
- Structured data extraction using LLM-powered parsing with Zod/JSON schema definitions
- Screenshot capture for visual analysis
- Official MCP server with 5,200+ GitHub stars, one of the most popular MCP integrations available
- SDKs: Python, JavaScript, Go, Rust, Ruby
Limitations
- Stealth and anti-bot bypass are not included by default, you'll hit Cloudflare blocks on a meaningful percentage of sites at scale. Proxy configuration or higher-tier plans are needed for better success rates.
- No brand intelligence, no way to get logos, brand colors, or company metadata.
- Credit consumption varies by feature, making cost prediction harder.
Pricing
- Free tier: 1,000 credits/month
- Hobby: $16/month (5,000 credits, billed yearly)
- Standard: $83/month (100,000 credits, billed yearly)
- Scale: $599/month (1,000,000 credits, billed yearly)
Best for: Developers who want the most mature LangChain/LlamaIndex integration, strong recursive crawling, and a large community. The go-to if anti-bot bypass and brand data aren't requirements.
3. Spider.cloud
Spider.cloud is a high-performance web crawling API built in Rust. It claims speeds of up to 100,000 pages per second and positions itself as the fastest scraping API on the market.
Key Features
- Returns content in Markdown, HTML, plain text, JSON, or PDF
- Smart rendering that auto-detects whether a page needs a headless browser
- AI-powered structured extraction using vision models that analyze the rendered page
- Built-in CAPTCHA solving (reCAPTCHA, Cloudflare Turnstile)
- Sitemap support across all endpoints
- Streaming results for large crawls
- MCP server available
- SDKs: Python, JavaScript, Rust
Pricing
- Credit-based with no subscription required
- ~$0.48 per 1,000 pages (bandwidth + compute)
- Free credits on signup, no credit card required
- Credits never expire
Limitations
- Smaller community and ecosystem than more established tools
- No marketplace of pre-built scrapers
- Pricing can be unpredictable due to variable bandwidth + compute model
- No brand intelligence features
Best for: High-volume crawling jobs where raw speed is the priority and you need affordable per-page pricing.
4. Jina AI Reader
Jina AI Reader takes the simplest possible approach to web scraping for AI: prefix any URL with r.jina.ai/ and get back clean Markdown. No SDK, no configuration, no API keys required for basic usage. It's the fastest way to go from URL to LLM-ready text.
# That's it. No API key, no SDK, no configuration.
curl https://r.jina.ai/https://example.comKey Features
- Zero-config Markdown conversion, prefix a URL and you're done
- Strips navigation, ads, and HTML noise automatically
- Supports Shadow DOM extraction and iframe inclusion
- CSS selector targeting for focused extraction
- Screenshot and full-page capture modes
- EU-compliant endpoint available
- Official MCP server with URL-to-markdown, web search, and image search tools
- SDKs: Python, JavaScript (though the prefix API means any HTTP client works)
Pricing
- Free: 10 million tokens for new API keys, 100 RPM
- Paid: ~$0.02 per million tokens (token bundles)
- Pay-as-you-go, no subscription required
Limitations
- Single-page only, cannot crawl entire sites or follow links
- No structured data extraction (returns raw Markdown only)
- No sitemap crawling
- Rate limits shared across all Jina APIs
- No anti-bot bypass for protected sites
Best for: Quick, one-off page-to-Markdown conversion for LLM prompts. The best option for prototyping and scripts where you want zero setup, but limited for production-scale applications.
5. Crawl4AI
Crawl4AI is an open-source Python crawler built specifically for RAG pipelines. If you want full control over your scraping infrastructure without paying per-request fees, Crawl4AI is an excellent option.
Key Features
- Generates clean Markdown optimized for RAG with BM25-based content filtering
- LLM-powered structured extraction with any model (open-source or proprietary)
- Full-site crawling with link following and depth control
- Parallel crawling, session reuse, stealth mode
- Crash recovery and prefetch mode for faster URL discovery
- Community-built MCP servers available (not official)
- SDKs: Python only
Pricing
- Open-source core: Completely free
- Managed platform: $1 per 1,000 pages
- Pro: $99/month with advanced proxies and unlimited concurrency
Limitations
- Self-hosted version requires managing your own infrastructure
- Steeper learning curve than hosted API solutions
- Python only, no JavaScript/TypeScript or Go SDK
- No built-in anti-bot bypass at the level of commercial providers
- No brand intelligence
Best for: Teams with Python expertise who want self-hosted, customizable scraping with no per-request costs. Ideal for RAG pipelines with large crawl volumes.
6. Apify
Apify is a full-stack web scraping and automation platform with a marketplace of 10,000+ pre-built scrapers called "Actors." It's less of a simple API and more of a cloud compute platform for running web automation.
Key Features
- Website Content Crawler converts pages to Markdown, stripping noise
- Multiple crawling backends (Playwright for JS-heavy, Cheerio for fast HTTP)
- Built-in sitemap detection and parsing
- 10,000+ pre-built Actors for specific sites (Amazon, LinkedIn, Google, etc.)
- Scheduling, scaling, and monitoring built in
- Official MCP server for exposing Actors to AI clients
- Open-source Crawlee SDK for custom scrapers
- SDKs: JavaScript, Python
Pricing
- Free: $5/month platform credit (forever free)
- Starter: $19/month
- Scale: $199/month
- Business: $999/month
- Pay-as-you-go compute on top of plan
Limitations
- Significant learning curve for the Actor model and platform
- Costs add up quickly at scale (compute + proxy + storage)
- Pre-built Actors vary in quality and maintenance
- Platform lock-in
- More platform-heavy than a simple URL-to-Markdown API
Best for: Teams that need pre-built scrapers for specific websites or complex automation workflows beyond simple page extraction.
7. ScrapingBee
ScrapingBee focuses on simplicity, it handles headless browsers and rotating proxies behind a single API call. Point it at a URL and get back HTML, with options for screenshots and JavaScript execution.
Key Features
- JavaScript rendering for SPAs (React, Angular, Vue)
- Proxy pool with automatic rotation and geolocation
- AI web scraping feature for plain-English data extraction
- Google Search API and Amazon scraping
- Custom JavaScript snippet execution on pages
- Markdown, JSON, and plain text output options
- MCP server available
- SDKs: Python, JavaScript
Pricing
- Free trial: 1,000 API credits, no credit card required
- Freelance: $49/month (250,000 credits)
- Startup: $99/month (1,000,000 credits)
- Business: $249/month (3,000,000 credits)
Limitations
- Default 5 credits per request, actual page count is 1/5 of credit count
- Some advanced rendering, proxy, and geotargeting features vary by plan
- Credits don't carry over month to month
- Blocked requests may still consume credits
- No full-site crawling
Best for: Developers who want a simple, no-frills scraping API and don't need full-site crawling or advanced AI features.
8. Oxylabs
Oxylabs combines a web-scraping API with large-scale proxy infrastructure, including a network of more than 175 million residential IPs. Its success-based pricing means failed requests do not consume quota, making it a strong option for teams that prioritize access reliability and proxy scale.
Key Features
- Web Scraper API with built-in proxy rotation and anti-bot handling
- 175M+ residential IPs
- Success-based pricing, so failed requests do not consume quota
- OxyCopilot prompt-based assistant for AI-assisted scraper setup and extraction
- SDKs: Python, Go
Pricing
- Web Scraper API: starts at $49/month
- Failed requests do not consume quota
Limitations
- OxyCopilot is an add-on convenience feature rather than a native LLM data pipeline
- No native Markdown or LLM-ready output
- No general-purpose MCP server for AI agents or clients
- Proxy infrastructure is the main differentiator, making the platform heavier than a focused AI scraping API
Best for: Teams that need large-scale proxy infrastructure alongside scraping. It is a weaker fit for teams primarily seeking AI-native output or direct agent-tool integration.
9. Zyte
Zyte offers a mature scraping and ban-handling API with prices based on site difficulty and successful responses. The company also creates and maintains Scrapy, making Zyte especially relevant to teams already using that open-source Python crawling framework.
Key Features
- Automatic ban handling, CAPTCHA handling, proxy rotation, and JavaScript rendering
- Built-in AI-powered structured extraction
- Tiered billing based on site difficulty and response type
- Charges only for successful responses
- Tight integration with Scrapy through its Python tooling
- Agentic Web Data plugin for Claude Code
- SDKs: Python
Pricing
- Prices range from $0.06 per 1,000 successful simple HTTP responses with a qualifying commitment to $16.08 per 1,000 pay-as-you-go browser-rendered responses on the most complex sites
- No subscription commitment is required for pay-as-you-go usage
- New accounts receive $5 in free trial credit
Limitations
- Tiered site-difficulty pricing is harder to predict than a flat-rate plan
- Output focuses on HTTP bodies, browser HTML, screenshots, and structured fields rather than native Markdown
- The Agentic Web Data plugin is specific to Claude Code, not a general-purpose MCP server available to any AI client
- Best suited to Python and Scrapy workflows
Best for: Teams that need mature enterprise unblocking and want to pay according to site difficulty. It is less suitable for teams seeking simple flat-rate pricing or broad MCP-based agent integration.
10. ZenRows
ZenRows specializes in one thing: getting through anti-bot protections. If the site you need to scrape is behind Cloudflare, DataDome, or PerimeterX, ZenRows is built to handle it.
Key Features
- LLM-optimized Markdown output that minimizes tokens while preserving context
- "Autoparse" feature converts unstructured content to structured JSON automatically
- Scraping Browser (cloud Puppeteer/Playwright with anti-bot built in)
- 55M+ residential proxy IPs with geotargeting
- Handles Cloudflare, DataDome, PerimeterX, and other anti-bot systems
- SDKs: Python, JavaScript
Pricing
- Free trial: 1,000 URLs (14 days)
- Developer: $69/month (250K basic results, 10K protected results)
- Startup: $129/month (1M basic results, 40K protected results)
- Cost multipliers for JS rendering and premium proxies
Limitations
- "Protected results" have a separate, much smaller quota
- Cost multipliers make real pricing hard to predict
- No full-site crawling or link following
- No MCP server
- Less focused on AI/LLM features than competitors
Best for: Scraping heavily protected sites where other tools fail. Strong anti-bot bypass, but less compelling for general-purpose AI scraping.
11. Bright Data
Bright Data is the largest web data platform in the world, with 150M+ residential IPs across 195 countries. It's more of an enterprise data infrastructure provider than a simple scraping API.
Key Features
- Largest proxy network in the industry (150M+ residential, datacenter, ISP, mobile)
- 437+ pre-built scrapers for specific domains (Amazon, LinkedIn, TikTok, etc.)
- Web Unlocker for anti-bot bypass (98%+ success rate)
- Scraping Browser (cloud headless browser)
- Dataset marketplace with ready-made datasets
- SERP API and Social Media API
- SDKs: Python, JavaScript
Pricing
- Pay-as-you-go: starts at $1.50 per 1,000 results
- Web Scraper IDE: from $500/month
- Proxies: residential from $5.04/GB
Limitations
- Enterprise pricing puts it out of reach for most teams
- Complex product lineup with steep learning curve
- Not LLM/AI-native, no Markdown-first output or agent integrations
- Proxy-centric model means you're paying for bandwidth
- Overkill for simple scraping tasks
- No MCP server
Best for: Enterprise-scale data collection operations that need massive proxy infrastructure and pre-built scrapers for specific platforms.
Also Considered: Diffbot
Diffbot takes a fundamentally different approach: instead of returning raw content, it uses machine learning and computer vision to automatically classify pages and extract structured data. It also provides one of the world's largest Knowledge Graphs (10B+ entities).
Key Features
- Automatic page classification (Article, Product, Discussion, Image, Video)
- ML-powered structured extraction without selectors or prompts
- Knowledge Graph with 264M+ organizations, 1.6B+ articles, 3M+ products
- NLP for entity recognition, relationship extraction, sentiment analysis
- Full-site crawling via Crawlbot
- SDKs: Python, JavaScript
Pricing
- 14-day free trial (full API access)
- Startup: $299/month
- Plus: $899/month
- Credit-based system with overage charges
Limitations
- Expensive, $299/month minimum makes it inaccessible for small teams
- Not optimized for LLM/Markdown output (structured JSON focus)
- No AI agent or LangChain integrations
- No MCP server
- Enterprise-oriented, not ideal for prototyping
Best for: Enterprise teams that need structured data extraction at scale and can leverage the Knowledge Graph for data enrichment.
Example: Building a RAG Pipeline with Context.dev
Here's what a typical RAG ingestion workflow looks like using Context.dev as your single data source:
import ContextDev from 'context.dev';
const client = new ContextDev({ apiKey: process.env.CONTEXT_DEV_API_KEY });
// 1. Discover all pages on a documentation site
const { urls } = await client.web.webScrapeSitemap({ domain: 'docs.example.com' });
// 2. Scrape each page as clean Markdown
const pages = await Promise.all(urls.slice(0, 100).map((url) => client.web.webScrapeMd({ url })));
// 3. Enrich with brand context for the company
const brand = await client.brand.retrieve({ type: 'by_domain', domain: 'example.com' });
// 4. Chunk, embed, and store in your vector database
for (const page of pages) {
const chunks = chunkMarkdown(page.markdown);
const embeddings = await embed(chunks);
await vectorDB.upsert(embeddings, {
brand: brand.brand.title,
industry: brand.brand.industries,
});
}
// One API for scraping, brand data, and AI extraction, no glue codeThis workflow would require 2-3 separate services with any other tool on this list: a scraper for the content, a brand data provider for company context, and potentially a separate AI extraction service for structured data.
Which Tool Should You Pick?
Different projects have different needs. Here's a quick guide:
- Building RAG pipelines or AI agents that need clean web data? Context.dev or Firecrawl are your best options. Context.dev has better anti-bot handling out of the box; Firecrawl has a more mature LangChain/LlamaIndex ecosystem and recursive crawling.
- Need brand data (logos, colors, company info) alongside web scraping? Context.dev is the only tool that handles this natively. Every other option requires a separate service.
- Need an MCP server for AI agent integration? Context.dev, Firecrawl, Spider.cloud, Jina Reader, Apify, and ScrapingBee all have MCP options. Firecrawl's is the most widely adopted in the AI scraping niche.
- Scraping heavily protected sites (Cloudflare, DataDome)? ZenRows and Bright Data specialize in this. Context.dev includes it by default at no extra cost.
- Budget-constrained or want self-hosted? Crawl4AI is open-source and free. Jina Reader's free tier is generous for prototyping.
- Need pre-built scrapers for specific platforms (Amazon, LinkedIn)? Apify's Actor marketplace or Bright Data's pre-built scrapers are the way to go.
- Need large-scale proxy infrastructure alongside scraping? Oxylabs combines its Web Scraper API with a residential proxy network of more than 175 million IPs and does not charge quota for failed requests.
- Need enterprise-grade unblocking with granular per-site pricing? Zyte provides mature ban handling and bills per successful response based on site difficulty, making it a strong fit for teams that prefer granular usage pricing.
- Enterprise-scale with massive proxy needs? Bright Data has the largest infrastructure. Diffbot is strong if you need a Knowledge Graph.
- Just need quick page-to-Markdown for prototyping? Jina Reader, prefix the URL and you're done.
Why Context.dev Is the Best All-in-One Scraping API for AI
If you're building AI applications that need web data, Context.dev is a strong all-in-one option. It combines Markdown extraction, dedicated scraping APIs, schema-based and product extraction, brand intelligence, and an MCP server in a single platform with predictable pricing. That said, it's a newer player, and teams already invested in Firecrawl's ecosystem may prefer to stick with what they know.
Firecrawl is a strong choice for teams using LangChain/LlamaIndex, its ecosystem integrations and recursive crawling are best-in-class. For budget-conscious teams, Crawl4AI's open-source approach or Jina Reader's generous free tier are worth exploring. And for enterprise-scale operations with serious proxy needs, Bright Data, Oxylabs, Zyte, and ZenRows fill that niche.
Try Context.dev free → | View pricing →
Pricing information accurate as of September 2026. Check each provider's website for current rates.
Methodology & Editorial Transparency
This comparison was compiled by the Context.dev engineering team to evaluate web scraping APIs specifically for AI and RAG architecture. All 11 ranked platforms were assessed across five standardized technical benchmarks: Markdown output fidelity, JSON Schema/Zod extraction compliance, Cloudflare/DataDome anti-bot bypass, native MCP server support, and cost-per-10k-pages. Tool specifications, SDK capabilities, and pricing are verified against public documentation, open-source repositories, and live API endpoints as of September 2026. While Context.dev is the publisher of this guide, every provider is evaluated against the same empirical engineering criteria.
FAQ
What is a web scraping API?
A web scraping API is a hosted service that extracts content from websites on your behalf. Instead of managing headless browsers, proxies, and anti-bot systems yourself, you send a URL to the API and get back the page content in your preferred format (HTML, Markdown, JSON, or screenshots). For AI applications, the most important capability is converting messy web pages into clean, structured data that LLMs can consume directly.
Can web scraping APIs bypass Cloudflare and other anti-bot systems?
Some can, but it varies widely. Context.dev, Spider.cloud, Oxylabs, Zyte, ZenRows, and Bright Data include built-in anti-bot or ban-handling capabilities. Firecrawl, Apify, and ScrapingBee offer it as an add-on or on higher tiers. Jina Reader and Crawl4AI have limited or no anti-bot capabilities. If you're scraping at scale, anti-bot handling is critical, expect 20-40% of popular sites to use some form of bot protection.
What's the best web scraping API for RAG pipelines?
For RAG, you need clean Markdown output, sitemap crawling (to discover all pages on a site), and ideally structured metadata. Context.dev and Firecrawl are the strongest options. Context.dev adds brand intelligence (useful for metadata enrichment) and built-in anti-bot bypass. Firecrawl has better recursive crawling for sites without clean sitemaps. Crawl4AI is worth considering if you want a self-hosted, open-source solution.
What is MCP and why does it matter for web scraping?
MCP (Model Context Protocol) is a standard that allows AI agents to call external tools directly. An MCP-compatible scraping API means your AI agent can decide to scrape a page, extract data, or look up brand information without you writing custom integration code. Context.dev, Firecrawl, Spider.cloud, Jina Reader, Apify, and ScrapingBee all offer MCP options. This is increasingly important as AI agent frameworks mature.
How much do web scraping APIs cost?
Pricing ranges from free (Crawl4AI, Jina Reader's free tier) to enterprise-level ($500+/month for Bright Data and Diffbot). Most tools use a credit model. Context.dev's current paid plans are Developer at $25/month for 10,000 credits, Pro at $149/month for 200,000, and Scale at $499/month for 1,000,000. Firecrawl starts at $16/month for 5,000 credits when billed yearly. Check credit multipliers carefully because some tools charge more for rendering or anti-bot features.
Can I use web scraping APIs to scrape any website?
Web scraping APIs are tools, what you scrape is your responsibility. Most APIs respect robots.txt by default, and you should always comply with a website's terms of service. Common legitimate use cases include indexing public documentation for RAG, monitoring your own brand across the web, competitive pricing analysis, and academic research. Avoid scraping personal data, copyrighted content behind paywalls, or anything that violates applicable laws.