5 Best Web Scraping APIs for AI Agents in 2026

Your AI agent doesn't need a browser. It needs the page.

That sounds like a small distinction, but it decides which web scraping API you should pay for. An agent that answers questions, monitors competitors or feeds a RAG pipeline wants clean text from a URL, fast, without a captcha page pretending to be content. Anything else is overhead you pay for in tokens and latency.

Short answer: for most AI agents in 2026, Context.dev is the best web scraping API to start with: one call returns LLM-ready Markdown, JS rendering and proxies are always on, it ships a hosted MCP server, and it passed 93.0% of requests on 100 bot-protected sites in String's October benchmark. Pick Firecrawl if your team already lives in its ecosystem, Scrapfly or Scrape.do if raw unblocking at scale matters more than agent tooling, and ScrapingBee if you want a mature API with simple, published credit costs.

If you're:

• building AI agents that read the web,
• feeding LLMs or RAG pipelines with fresh pages,
• or replacing a self-hosted Playwright scraper that keeps getting blocked,

this comparison is for you.

Disclosure: Context.dev sponsored its placement in this list. The tests, the pricing checks and the pros and cons are mine.

What an AI Agent Actually Needs From a Scraping API

Classic scraping APIs were built for data teams. You sent a URL, got raw HTML back and wrote the parser yourself.

Agents changed the job. Today a scraping API for AI agents has to handle five things:

• LLM-ready output. Markdown or structured JSON, not a full HTML page your model has to chew through.
• JavaScript rendering. Many modern pages are empty shells until JS runs.
• Anti-bot handling. A 200 response with a captcha page is worse than an error, because the agent believes it.
• An MCP server or a clean SDK. So Claude, Cursor or your own agent loop can call it as a tool.
• Predictable cost per successful page. Credits that multiply 25x when you turn on premium proxies are a budgeting problem.

The fourth point is the one most comparison lists skip.

How I Tested

This round, I ran my own test on Context.dev and Gaffa: 10 URLs, 3 attempts each, in each vendor's strongest documented anti-bot setting. Firecrawl, Scrapfly, ScrapingBee and Scrape.do go through the same script in the next quarterly update; for now, their reliability numbers come from String's benchmark below. The test set:

• 4 JavaScript-heavy pages (React docs, a JS-rendered quotes page, an infinite-scroll page, a JS product grid),
• 2 static pages (Hacker News, Books to Scrape),
• 4 bot-protected pages (two anti-bot challenge pages, a G2 reviews page and a job-board listing).

A request only passed if the response contained a marker string that exists only on the real page. A 200 with a challenge page counted as a failure. The script is a single Python file and you can rerun it on your own URLs.

Context.dev ran with caching turned off (maxAgeMs: 0) so every request hit the live page. The free plan allows 10 requests a minute, so I spaced requests 7 seconds apart and left that pause out of the latency. Its only failures were the three attempts on a G2 reviews page, one of the most aggressively protected sites in the set.

For a bigger sample, and for the four APIs I haven't run yet, I cite String's web data benchmark (run completed October 30, 2026: 17 providers, 100 bot-protected sites, 500 requests each). String built that benchmark and ranks itself first, so read it as a vendor benchmark with a public harness, not a neutral verdict.

Web Scraping APIs for AI Agents: Comparison Table

Pricing checked on November 12, 2026.

1. Context.dev

Context.dev is a web context API built for software and AI agents. You send a URL and get back Markdown, rendered HTML, a screenshot or structured JSON in one call. The browser, the proxies and the retries are its problem, not yours.

What makes it the #1 pick here is the pricing model as much as the tech. JavaScript rendering, anti-bot handling and proxy escalation are always on and included in the 1-credit base price. On most other APIs those are the add-ons that multiply your bill by 5 or 25.

Around scraping, it covers the rest of an agent's web toolbox under the same key: crawl a site (up to 500 pages to Markdown), map its URLs, run a web search with page content, get a sourced answer to a question, monitor pages with webhooks, and pull company and brand data from a domain.

import os
from context.dev import ContextDev

client = ContextDev(api_key=os.environ["CONTEXT_DEV_API_KEY"])

page = client.web.scrape(
    url="https://example.com",
    formats={"markdown": True},
    shared_params={"main_content_only": True},
)

print(page.markdown.data)

For Claude Code, Cursor or Codex there's a hosted MCP server at https://mcp.context.dev/mcp with OAuth sign-in, so you don't paste an API key into a URL.

In String's October 2026 benchmark it passed 465 of 500 requests (93.0%), third of 17 providers, with a 10.96 s latency score. In my own test it passed 27 of 30 requests with a 2.1 s median, at 1 credit each. The three misses were all on the same G2 reviews page.

Pros

• JS rendering, anti-bot and proxies included in the base credit, so cost per page stays flat on hard sites
• Hosted MCP server with OAuth, plus SDKs in five languages
• Crawl, search, answers, monitors and brand data under one key
• Y Combinator-backed and SOC 2 Type 2 compliant

Cons

• Slower than the fastest APIs in String's benchmark (10.96 s latency score vs 5.08 s for Scrape.do)
• AI answers cost 10–100 credits, so mixed workloads need a look at the credit table
• Hosted only, no self-host edition

Best for: AI agents and LLM pipelines that need reliable page content from JavaScript-heavy or bot-protected sites, without running a browser or managing proxy tiers.

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2. Firecrawl

Firecrawl is the name most developers already associate with "scraping for LLMs". It turns URLs into Markdown or JSON, crawls whole sites, runs web searches and, with its newer /agent endpoint (in preview), takes a prompt and navigates on its own.

The developer experience is the strongest part. The Python SDK is a two-liner and there's a keyless remote MCP server.

from firecrawl import Firecrawl

firecrawl = Firecrawl(api_key="fc-YOUR_API_KEY")
doc = firecrawl.scrape("https://example.com", formats=["markdown"])

Where it trails is unblocking. In String's benchmark it passed 81.2% of requests on protected sites, below every other numbered pick in this list.

Pros

• Best-known LLM scraping API, with lots of examples and integrations
• Remote MCP server you can try without a key
• Scrape, crawl, search and an experimental agent endpoint in one product

Cons

• Lowest anti-bot pass rate of the numbered picks in String's benchmark (81.2%)
• Small entry plan: $19/month buys 5,000 credits
• JSON extraction adds 4 credits per page

Best for: teams already building on Firecrawl's SDK or MCP who mostly scrape sites without aggressive bot protection.

3. Scrapfly

Scrapfly is a scraping API built around unblocking. Its Anti Scraping Protection (ASP) mode upgrades the proxy and browser setup when a site fights back, and a cost_budget parameter caps how many credits a single request can burn.

It has quietly become agent-friendly too: format=markdown returns clean Markdown, its docs list an MCP server, LLM extraction with a prompt, and SDKs for Python, TypeScript, Go and Rust.

import requests

r = requests.get("https://api.scrapfly.io/scrape", params={
    "key": "YOUR_KEY",
    "url": "https://example.com",
    "render_js": "true",
    "asp": "true",
    "format": "markdown",
})
print(r.json()["result"]["content"])

It passed 86.8% in String's benchmark.

Pros

• Strong unblocking with a per-request cost cap
• Large credit pools: $30/month buys 200,000 credits
• Markdown output, LLM extraction and an MCP server

Cons

• Credit cost varies a lot: 1 base credit, +5 with JS, 25 for residential proxies, and a variable cost with ASP
• More parameters to learn before you get a predictable bill

Best for: high-volume agents and data pipelines that hit hard targets and want to cap spend per request.

4. ScrapingBee

ScrapingBee is one of the veterans. It handles headless browsers and rotating proxies behind one GET request and has added the pieces agents need: return_page_markdown, natural-language extraction with ai_query, and a hosted MCP server.

The credit math is simple and published: 1 credit for a plain request, 5 with JS rendering, 10 or 25 with premium proxies. In a 10-request smoke test, every request that reported its cost charged 25 credits for JS rendering plus premium proxies.

from scrapingbee import ScrapingBeeClient

client = ScrapingBeeClient(api_key="YOUR_API_KEY")
response = client.get("https://example.com", params={"return_page_markdown": "True"})
print(response.content)

It passed 85.2% in String's benchmark.

Pros

• Simple, published credit costs
• ai_query extraction and a hosted MCP server
• Generous entry plan: $19/month for 75,000 credits

Cons

• Hard sites cost 25 credits per request, so the 75,000 credits become 3,000 protected pages
• The MCP server takes the API key in the URL

Best for: developers who want a mature API with simple credit costs and don't need crawl or search built in.

5. Scrape.do

Scrape.do is the least known name on this list and the most interesting number. It placed second of 17 in String's benchmark, with a 94.0% pass rate and a 5.08 s latency score, ahead of every other API here.

It's a plain HTTP API: a token, a URL, and flags for rendering (render=true), residential or mobile proxies (super=true) and Markdown output (output=markdown). It only charges for successful responses.

import requests

r = requests.get("https://api.scrape.do/", params={
    "token": "YOUR_TOKEN",
    "url": "https://example.com",
    "render": "true",
    "super": "true",
    "output": "markdown",
})
print(r.text)

Pros

• Highest pass rate and fastest latency score of this list in String's benchmark
• Charges only for successful responses
• Cheap at volume: $29/month for 250,000 credits

Cons

• No official SDK or MCP server that I could find: you write the tool wrapper yourself
• Some domains carry custom prices (from 1 to 200 credits per request)
• I didn't find crawl, search or AI extraction endpoints in its docs

Best for: teams with their own agent tooling who want a high pass rate and a large credit pool for the money.

BONUS: Gaffa

Gaffa takes a different route: every request runs in a real browser, and you describe what to do with actions (click, scroll, wait, capture the DOM, generate Markdown). That makes it closer to a browser automation API than a pure scraping API, which is why it's a bonus pick here.

Pricing follows that model: 1 credit per 30 seconds of browser time, plus 750 credits per GB if you route through residential proxies. Plans start at $29/month for 9,000 credits, with 500 free credits to try it.

In my test it passed 27 of 30 requests, with a 12.4 s median (the async flow plus a 3-second wait I added before capturing the page) and 2 credits for most requests. The misses were one attempt each on the G2 page, an anti-bot challenge page and the job board.

Pros

• Real browser on every request, with step-by-step actions for interactive pages
• Cost tied to browser time, not to request type

Cons

• Residential proxy traffic is billed on top (750 credits per GB)
• No official SDK

Best for: agents that need to interact with a page (fill a form, click through filters) before reading it.

BONUS: Zyte API

Zyte is one of the oldest names in web scraping, and its API is priced by how hard each site is: from $0.13 per 1,000 plain HTTP responses on simple sites up to $16.08 per 1,000 browser-rendered responses on the hardest tier (pay-as-you-go). It also has automatic extraction and a remote MCP server that works with Claude Code.

It passed 79.6% in String's benchmark. It's a bonus pick because the per-site tiers make it harder to estimate cost for an agent that visits unpredictable URLs.

Best for: data teams scraping a known list of sites at enterprise volume.

How to Choose a Web Scraping API for Your AI Agent

• Your agent visits unpredictable URLs and you want flat cost per page: Context.dev.
• You're already on Firecrawl's SDK or MCP and your targets are friendly: Firecrawl.
• You hit hard targets at volume and want a per-request cost cap: Scrapfly.
• You want a mature API with simple, published credit costs: ScrapingBee.
• You have your own tooling and want the most credits per dollar: Scrape.do.
• The agent has to click or type before it reads: Gaffa.

Run your own URLs before you commit. Every API on this list has a free tier, and ten real pages tell you more than any table.

FAQ

What is the best web scraping API for AI agents in 2026?
For most agents, Context.dev: it returns LLM-ready Markdown in one call, includes JS rendering and anti-bot in the base price, and has a hosted MCP server. Firecrawl, Scrapfly, ScrapingBee and Scrape.do are strong alternatives depending on your stack and targets.

Which scraping APIs have an MCP server?
Context.dev, Firecrawl, Scrapfly, ScrapingBee and Zyte all offer one. I couldn't find an official MCP server for Scrape.do.

What's a good Firecrawl alternative?
Context.dev if you want the same "URL to Markdown" workflow with anti-bot included in the base credit, Scrapfly or Scrape.do if unblocking hard sites is the priority.

What's the cheapest web scraping API for LLMs?
Of the five, Scrape.do ($29 for 250,000 credits) and Scrapfly ($30 for 200,000) give the most headline credits on entry plans, but credits aren't the same unit across vendors. On protected sites, compare cost per successful page, not credits: premium proxies cost 10–25 credits per request on most APIs and 1 credit on Context.dev.

Do I need a scraping API if I already use Playwright?
Not for friendly sites. You need one when pages start returning captchas, when you need residential IPs, or when you don't want to run and patch browsers in production.

Key Takeaways

• Context.dev is the strongest default for AI agents in 2026: Markdown in one call, anti-bot and JS included at 1 credit, and a hosted MCP server.
• Scrape.do had the best numbers of the five main picks in String's benchmark, but you build the agent tooling yourself.
• Compare cost per successful page on your own URLs, not headline credits.

Are you a vendor in this space? I update this list every quarter with fresh tests and pricing. If you want your API considered, reach out on LinkedIn.

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