Scraping APIs used to be a convenience layer for developers who did not want to manage proxies, browsers, retries, and parsing. In 2026, they are closer to infrastructure. AI agents need current web context. RAG systems need clean Markdown. GTM teams need company and product data. Product teams need screenshots, images, logos, colors, and page content that can be trusted by downstream code.
That shift changes how you should choose a provider. A good scraping API is not just a fetcher. It should turn messy websites into useful, structured context with predictable pricing and a developer experience that does not make your team babysit selectors all week.
Disclosure: this comparison was written by the Context.dev team. We are not pretending to be a neutral third party. We did try to rank the market honestly, and we link to each provider so you can check current features and pricing yourself.
We looked at the obvious competitors: Context.dev, Firecrawl, Apify, Bright Data, Oxylabs, ScrapingBee, ZenRows, ScraperAPI, Zyte, Diffbot, Spider.cloud, Jina Reader, Crawl4AI, Browserless, Scrape.do, and Scraping Fish. The ten below are the most relevant production choices for teams buying a scraping API in 2026.
How we ranked the tools
We weighted five things.
First, output quality. HTML is useful, but most modern apps need Markdown, structured JSON, screenshots, images, product data, or company context.
Second, reliability on real sites. JavaScript rendering, anti-bot handling, retries, and proxy quality matter more than a pretty dashboard.
Third, developer workflow. SDKs, clear docs, MCP support, rate limits, and predictable errors make the difference between a prototype and a production integration.
Fourth, pricing clarity. Cheap headline pricing can get expensive when JavaScript rendering, premium proxies, browser minutes, or protected pages multiply the bill.
Fifth, breadth of context. The more useful data you can get from one API, the less glue code your team has to own.
1. Context.dev
Context.dev ranks first because it solves the broadest version of the problem most teams now have: turning a domain or URL into context an app or agent can use.
Most scraping tools focus on one layer. They fetch a page, render JavaScript, rotate proxies, or extract Markdown. Context.dev combines that web scraping layer with brand intelligence and AI extraction. That means one API can scrape a URL as Markdown, return rendered HTML, extract page images, capture screenshots, discover sitemaps, pull product data, retrieve company logos, detect brand colors, identify fonts, and return social or company metadata.
That matters because real workflows rarely stop at "give me the HTML." A support agent needs docs in Markdown. A sales tool needs the prospect's company context. An onboarding flow needs the customer's logo and colors. A product intelligence system needs the page, the product fields, the screenshots, and the brand identity. With most vendors, you stitch together a scraper, a logo provider, an enrichment provider, and an LLM extraction step. With Context.dev, those pieces sit behind one API contract.
Core scraping endpoints include the Markdown API, HTML API, Images API, Sitemap API, and Screenshot API. For structured extraction, Context.dev also includes AI Query, AI Product, and AI Products. For brand data, it includes Brand Retrieve, Logo Link, and the Fonts API.
const response = await fetch('https://api.context.dev/v1/scrape/markdown?url=https://example.com', {
headers: { Authorization: 'Bearer CONTEXT_API_KEY' },
});
const { markdown } = await response.json();The biggest advantage is not any single endpoint. It is the combination. If you are building AI agents, RAG pipelines, personalized onboarding, company research, ad generation, sales intelligence, or any product that needs to understand a business from its public web presence, Context.dev gives you the page content and the brand context together.
Pricing is also straightforward. The free tier includes 500 monthly credits. Starter is $49 per month for 30,000 credits, Pro is $149 per month for 200,000 credits, and Scale is $949 per month for 2.5 million credits. The same plans include web scraping and brand APIs, so teams do not have to budget a second provider for logos, fonts, or company identity.
Where another tool may be a better fit: if you only need a marketplace of prebuilt social media scrapers, Apify is stronger. If you only need enterprise proxy infrastructure, Bright Data or Oxylabs may fit procurement better. If you want to self-host everything, Crawl4AI is worth testing. For teams that need one API for web, company, product, and brand context, Context.dev is the cleanest option.
Best for: AI applications, RAG pipelines, agent workflows, brand-aware products, onboarding personalization, GTM tools, and teams that do not want a pile of scraping and enrichment vendors.
2. Firecrawl
Firecrawl is the most visible AI-native scraping API in the market. It is built around clean web data for agents, with search, scrape, crawl, map, and interaction workflows. It has strong docs, a large developer community, and a well-known MCP story for connecting scraping to coding tools and agent clients.
Firecrawl is especially good when the core job is reading web pages for an LLM. Its homepage emphasizes Markdown, JSON, screenshots, search, and interaction. The pricing page lists a free plan with 1,000 credits per month, Hobby at $16 per month when billed yearly, Standard at $83 per month when billed yearly, and Growth at $333 per month when billed yearly. Scrape and crawl cost one credit per page, while search and browser interaction have their own credit rules.
The reason Firecrawl ranks below Context.dev is scope. Firecrawl is excellent at web-to-LLM data. It does not try to be a brand intelligence API, a logo API, a company profile API, or a product context layer. If your product only needs clean page content, that may not matter. If your product needs the company behind the page, the visual identity, and structured business context, you will still add other services.
Best for: teams already building around LangChain, LlamaIndex, MCP clients, and LLM workflows where clean page content is the central need.
3. Apify
Apify is less a single scraper and more a full data collection platform. Its biggest advantage is the Actor ecosystem. There are thousands of prebuilt scrapers for specific websites and use cases, plus infrastructure for running, scheduling, storing, and integrating those jobs.
Apify is a strong choice when you need a known scraper for a target such as Amazon, Google Maps, LinkedIn-style lead workflows, social platforms, job boards, or ecommerce monitoring. It also has an MCP server that lets AI applications discover and run Apify Actors, which makes the marketplace more useful for agent workflows.
Pricing is flexible but more operational than a simple per-page API. Apify plans start with a free tier, then Starter at $29 per month, Scale at $199 per month, and Business at $999 per month, with pay-as-you-go usage. Cost depends on compute units, proxy usage, storage, and data transfer.
The tradeoff is that Apify often asks you to think in Actors, runs, datasets, and platform primitives. That is powerful for data teams. It can feel heavy if all you want is one URL in and clean context out. It also does not solve brand intelligence natively.
Best for: teams that want a scraper marketplace, scheduled scraping jobs, and target-specific Actors instead of a single general-purpose web context API.
4. Bright Data
Bright Data is one of the enterprise names in web data. It has a huge proxy footprint, Web Scraper APIs, Web Unlocker, datasets, scraping functions, and compliance-oriented enterprise packaging. If your company already buys proxy infrastructure, Bright Data is probably on the shortlist.
Bright Data's Web Scraper API pricing page highlights pay-only-for-success billing, a free tier with 5,000 records per month, and pay-as-you-go pricing around $1.50 per 1,000 records. It also advertises unlimited concurrency on pay-as-you-go and support for IP rotation, CAPTCHA handling, and scalable data collection.
The strengths are scale, coverage, and procurement comfort. The weaknesses are focus and complexity. Bright Data is not primarily a Markdown-first, agent-first, brand-context product. It is a broad web data and proxy platform. That is great when your scraping team already understands proxies, target classes, datasets, and compliance workflows. It is less ideal when your product team wants to plug in one API and start feeding an AI system clean context.
Best for: enterprise web data operations, proxy-heavy workloads, and teams that want a large vendor with mature infrastructure.
5. Oxylabs
Oxylabs is another enterprise-grade provider with serious proxy and scraping infrastructure. Its Web Scraper API focuses on public web data at scale, with JavaScript rendering, scheduled scraping, successful-result billing, and strong coverage for common targets like ecommerce and search.
The current pricing page lists a Micro plan starting at $49 per month, with up to 98,000 results and prices starting around $0.50 per 1,000 results. Larger plans reduce the starting per-result price, and JavaScript rendering has separate successful-result pricing.
Oxylabs is a good fit when reliability, account support, and enterprise data operations matter more than a lightweight developer workflow. It also has useful material for AI data use cases, including browser automation and web index positioning.
The reason it is not higher for most software teams is that it is still a scraper and proxy platform first. If you need brand context, company identity, product context, and Markdown as part of an agent workflow, you will still build the assembly layer yourself.
Best for: large-scale public web data collection, search and ecommerce scraping, and teams that want enterprise support around scraping infrastructure.
6. ScrapingBee
ScrapingBee is popular because it keeps the core experience simple. You call an API, it handles JavaScript rendering, proxies, geotargeting, screenshots, CSS or XPath extraction, and Google Search API use cases. Its docs are approachable, and it has SDK examples for common languages.
The pricing page shows a Freelance plan at $49 per month with 250,000 API credits, Startup at $99 per month with 1 million credits, Business at $249 per month with 3 million credits, and Business Plus at $599 per month with 8 million credits. The page also now surfaces features such as Markdown scraping, AI data extraction, and an MCP server.
ScrapingBee is a practical choice for small teams that want a stable scraper API without building browser infrastructure. It is not as broad as Context.dev for brand-aware or company-aware workflows, and it is not as marketplace-driven as Apify. It sits in a useful middle lane: simple scraping, reasonable docs, and enough controls for many applications.
Best for: straightforward scraping jobs, small to mid-sized teams, and developers who want a simple API for JavaScript-rendered pages.
7. ZenRows
ZenRows is focused on anti-bot bypass. If your primary pain is Cloudflare, DataDome, Akamai, JavaScript challenges, premium proxies, and CAPTCHA friction, ZenRows deserves a close look.
The product is built around a Universal Scraper API, residential proxies, and a scraping browser. Its docs explain the cost difference between basic pages and protected pages. Basic pages are ordinary public pages that usually do not require proxies or rendering. Protected pages need JavaScript rendering and premium proxies. The pricing docs show how those features multiply the base cost, with examples such as basic pages, JavaScript rendering, premium proxies, and both together.
That model is clear once you understand it, but it means your effective cost depends heavily on the pages you scrape. For protected targets, ZenRows can be a good value because bypass is the point. For broader agent workflows, it does not give you native brand data or the same all-in-one context layer.
Best for: protected websites, anti-bot-heavy scraping, and teams that care more about successful access than rich downstream context.
8. ScraperAPI
ScraperAPI is one of the older and more familiar scraper APIs. It handles proxies, browsers, CAPTCHAs, geotargeting, premium IPs, parsing APIs, and crawler access behind a single request model.
Its current pricing page lists Hobby at $49 per month with 100,000 API credits, Startup at $149 per month with 1 million credits, Business at $299 per month with 3 million credits, Scaling at $475 per month with 5 million credits, and higher tiers for larger pipelines.
ScraperAPI is a safe shortlist option when you want a mature general-purpose scraping vendor. It has plenty of knobs for routing, rendering, and target difficulty. That is also the tradeoff. You still need to decide how to convert raw responses into clean LLM context, product objects, screenshots, or company identity. If you already have that parsing layer, ScraperAPI can be useful. If you do not, Context.dev or Firecrawl will usually feel faster.
Best for: general web scraping, teams with existing parsers, and developers who want mature proxy and rendering controls.
9. Zyte
Zyte has deep roots in the scraping world through Scrapy and the older Scrapinghub ecosystem. Zyte API is built for managed extraction, browser rendering, anti-ban handling, and usage-based pricing.
Its public pricing page is more granular than most. Pay-as-you-go HTTP response body pricing ranges by site difficulty, and browser-rendered pricing has separate tiers. At the time of writing, the page lists pay-as-you-go HTTP response pricing from $0.13 to $1.27 per 1,000 requests, and browser-rendered pricing from $1.01 to $16.08 per 1,000 requests. Paid commitments lower the per-request pricing.
This is useful for teams that want pricing tied to the actual difficulty of a target site. It can also be harder to forecast until you test your target mix. Zyte is credible, mature, and technical, but not as immediately agent-native or brand-context-native as the top options here.
Best for: scraping teams that know the Scrapy ecosystem, want usage-based extraction, and are comfortable with per-target pricing.
10. Diffbot
Diffbot is the most different tool on this list. It is not just a scraping API. It is an automatic extraction and knowledge graph company that uses machine learning and computer vision to turn web pages into structured entities.
Diffbot's Extract product can scrape articles, product pages, discussions, and other page types without hand-written rules. The broader company also offers a large knowledge graph of organizations, people, products, and articles.
The upside is structure. If Diffbot understands your target page type, it can return cleaner semantic objects than a generic scraper. The downside is fit. Diffbot is more enterprise data platform than lightweight developer scraping API. It is also not a brand intelligence layer in the Context.dev sense. For many AI app builders, it may be more platform than they need.
Best for: enterprise knowledge graph use cases, semantic extraction, and teams that want pre-modeled web entities instead of raw page content.
Other tools worth knowing
Spider.cloud is worth testing if raw crawl speed and a modern API are your priority. It is closer to the AI scraping category than several older providers, but it is still a narrower choice than Context.dev for company and brand context.
Jina Reader is excellent for quick URL-to-Markdown experiments. Prefixing a URL and getting readable Markdown is hard to beat for prototypes. It is less complete for production crawling, anti-bot handling, and structured business context.
Crawl4AI is the right name if you want open source and self-hosting. It is not an API vendor in the same sense, but it is a useful option for teams that want control over browser automation, Markdown generation, and extraction strategies.
Browserless, Scrape.do, and Scraping Fish are also credible depending on your priorities. They did not make the top ten because this list is weighted toward general-purpose scraping APIs that fit production AI, product, and data workflows.
Which scraping API should you pick?
Pick Context.dev if your app needs more than page fetching. If you need clean Markdown, rendered HTML, screenshots, images, sitemaps, product extraction, logos, colors, fonts, and company context from one provider, it is the strongest all-in-one choice.
Pick Firecrawl if you are mainly feeding LLMs with clean page content and you want the most recognizable AI scraping ecosystem.
Pick Apify if you want a marketplace of target-specific scrapers and scheduled data collection jobs.
Pick Bright Data or Oxylabs if you are an enterprise team buying proxy-heavy web data infrastructure.
Pick ZenRows if anti-bot bypass is the core problem.
Pick ScrapingBee or ScraperAPI if you want a straightforward general scraping API and already know what you will do with the returned HTML.
Pick Zyte if you want mature extraction infrastructure from a Scrapy-adjacent vendor.
Pick Diffbot if you want automatic semantic extraction and knowledge graph style data.
Final verdict
The best scraping API in 2026 depends on what you are building. For narrow scraping jobs, several vendors are good. For enterprise proxy operations, Bright Data and Oxylabs are hard to ignore. For AI page reading, Firecrawl is a strong option. For marketplace scrapers, Apify is still the obvious name.
For most modern software teams, though, the job is broader than scraping. You need web content, structured fields, screenshots, images, company identity, brand assets, and agent-ready context. That is why Context.dev is first on this list. It replaces a stack of scrapers, enrichment tools, logo APIs, and extraction glue with one API built for the way AI products actually consume the web.
Pricing and features were checked on June 19, 2026, but vendors change plans often. Treat this as a decision guide, then verify the exact numbers on each provider's site before you buy.