browser-use, but Unblocked and Managed.

Two honest, different shapes

browser-use and Human Browser both let an LLM drive a real browser — but one is a library you operate and the other is a service you call. The right pick depends on the job, and we will be straight about where each wins.

browser-use is one of the most popular open-source projects for LLM-driven browser automation: a free Python library (MIT) where you describe a task, plug in your own LLM, and it controls a real browser via Playwright under the hood. It is flexible, hackable and genuinely great — for local development, for low-protection targets, and for teams that want full control of the code and stack. What it deliberately does not bundle is the production anti-bot layer: residential IPs, fingerprint hardening, a CAPTCHA solver and the cloud to run it all on are yours to add and maintain.

Human Browser is a managed cloud built around that missing layer. You do not install a library or run a browser — you send a goal ("log into this dashboard and export the CSV") to an A2A (v0.3) endpoint or call it as an MCP tool, and a hosted agent on our own action layer plans and executes the steps. Residential IP across 75 countries, a stealth-patched headful Chrome, a 12-type CAPTCHA solver, persistent profiles and a live human-in-the-loop viewer are wired in by default, on one pay-as-you-go bill with no subscription.

If you want a free, open-source library to build and operate yourself, browser-use is purpose-built for that. If you keep hitting Cloudflare walls — or simply do not want to run and harden the infrastructure — Human Browser is the managed path with anti-bot included.

Where browser-use genuinely wins

We are not going to pretend otherwise — browser-use has real advantages, and for plenty of teams they are decisive:

Where it starts to hurt — and what Human Browser bundles

The friction with any run-it-yourself library shows up the moment a target fights back. A standard browser presents a datacenter IP, a default fingerprint and missing residential signals, so Cloudflare, DataDome and PerimeterX flag it — and now you are integrating a residential proxy provider, hardening fingerprints, wiring a CAPTCHA solver, and babysitting all three as defenses change. That is the work Human Browser absorbs.

For the technical detail on the anti-bot side, see our guides on bypassing Cloudflare with Playwright in 2026, why naive playwright-stealth stops working in 2026, and the best residential proxy for scraping in 2026.

Comparing the wider field? We keep an honest, regularly updated roundup of the best cloud browsers for AI agents and the best browser automation APIs, plus focused head-to-heads on Human Browser vs Browserbase, vs Steel.dev and vs Browserless.

Cost model comparison

The honest summary: on the price of the software, browser-use wins outright — it is free and open source — and on control and self-hosting it wins too. What Human Browser's pay-as-you-go price buys is everything around the browser: the managed cloud, residential IPs, always-on stealth, a CAPTCHA solver and a hosted A2A/MCP agent, so there is nothing to assemble or operate. You are choosing between "free library, you run and harden it" and "managed service, anti-bot included." Verify browser-use's current cloud terms on their site; both move over time.

When Human Browser is the right choice

• You keep getting blocked on Cloudflare/DataDome/PerimeterX targets and do not want to assemble and maintain a residential-proxy + stealth + CAPTCHA stack around a library.
• You do not want to run infrastructure — no browsers to host, no fleet to scale, no anti-bot to patch as defenses change.
• You are A2A- or MCP-first — your agent already speaks the protocol and you want a browser reachable as another agent or an MCP tool, in any language.
• You want a live viewer with real human takeover on every session, free, for the moments an agent needs a hand.
• You want one pay-as-you-go bill instead of stitching together compute, an LLM provider, a proxy vendor and a CAPTCHA service.

Code example: browser-use library vs Human Browser A2A

from browser_use import Agent
from browser_use.llm import ChatOpenAI
import asyncio

agent = Agent(
    task='Log into target.com, export CSV from /reports',
    llm=ChatOpenAI(model='gpt-4.1'),  # your key
)

# Runs a browser on your machine/server. No residential
# IP, stealth or CAPTCHA solver unless you wire them in.
result = asyncio.run(agent.run())

const res = await fetch('https://agent.humanbrowser.cloud/a2a', {
  method: 'POST',
  headers: {
    'Content-Type': 'application/json',
    'Authorization': 'Bearer ' + process.env.HB_TOKEN
  },
  body: JSON.stringify({
    jsonrpc: '2.0',
    id: 'login-1',
    method: 'tasks/send',
    params: {
      skill: 'login_and_scrape',
      message: 'Log into target.com, export CSV from /reports',
      country: 'gb',
      profile: 'reports-bot'
    }
  })
});
const { result } = await res.json();
// Residential IP, stealth, CAPTCHA, login, extraction handled.

The left side is the browser-use model: a free library plus the browser, LLM, proxy, stealth and CAPTCHA you supply and operate. The right side is the Human Browser model: a goal in, a result out, with the anti-bot stack and infrastructure included. Neither is wrong — they are aimed at different builders.

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