Browser Use
Lets AI do web tasks for you, such as filling forms, searching and extracting data, in the maker’s cloud browsers or on your computer.
Description from the maker (original English)
Stealth Chrome for AI agents: bot-protected sites, Turnstile, closed Shadow DOM, clean Markdown.
These three are never merged into one score: opinions, measurements and popularity are different things.
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
You need
Which app do you use?
Pick your app above. We remember it, so next time the button says “Install in …”.
Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"browser-scraper": {
"command": "npx",
"args": [
"-y",
"@eurafaeldecarvalho/browser-scraper",
"mcp"
]
}
}
}Run this in your terminal
claude mcp add browser-scraper -- npx -y @eurafaeldecarvalho/browser-scraper mcpPaste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"browser-scraper": {
"command": "npx",
"args": [
"-y",
"@eurafaeldecarvalho/browser-scraper",
"mcp"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"servers": {
"browser-scraper": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@eurafaeldecarvalho/browser-scraper",
"mcp"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.
Your choice stays on this device in a cookie; no account needed.
These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Runs on your computer; the tool list appears in your AI app after you install it.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026
The registry name was verified with the GitHub account eurafaeldecarvalho, which owns the repo
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
The registry does not list a required key, though some servers ask you to sign in on first use.
It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed –, and the latest version (0.8.3) reached the registry 10 days ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.
In the same category: Browser Use, Chrome DevTools MCP, MCP Server Browser
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
Lets AI do web tasks for you, such as filling forms, searching and extracting data, in the maker’s cloud browsers or on your computer.
Lets AI use Chrome’s developer tools to inspect pages, find what makes them slow and spot errors. Made by the Chrome DevTools team.
MCP server for browser use access
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
Undetected Chrome for Node.js that reads and operates the sites that block bots. Use it as a library, a CLI or an MCP server for Claude, Cursor and Codex. It turns any page, including closed Shadow DOM and cross-origin iframes, into clean Markdown, structured data or an accessibility snapshot an agent can click through. Local, free, MIT, bring-your-own-LLM.
CreepJS: 0% headless, 0% stealth · `bot.sannysoft.com`: 0 failures · no `Runtime.enable` leak (what that means, and where it stops)
Recorded on one desktop PC: the Turnstile test page at nowsecure.nl in headless mode, bot.sannysoft.com headful on the PC's own GPU.
import { scrape } from "@eurafaeldecarvalho/browser-scraper";
const page = await scrape({ url: "https://example.com", formats: ["markdown", "metadata"] }); console.log(page.tier); // "http" | "browser" | "stealth": the cheapest tier that worked console.log(page.markdown); // clean, LLM-ready Markdown of the main content
# Give Claude Code a browser that gets through Cloudflare:
claude mcp add browser-scraper -- npx -y @eurafaeldecarvalho/browser-scraper mcp
@eurafaeldecarvalho/browser-scraper drives real Chrome over the raw DevTools Protocol (CDP). It never sends Runtime.enable, one of the most widely fingerprinted automation signals, and every layer of the browser's identity tells the same story. On top of that stealth core it adds the pieces AI workloads need: Markdown and metadata extraction, an accessibility snapshot with clickable refs, a one-call scrape() that escalates from plain HTTP to a stealth browser only when it has to, an MCP server, and optional LLM extraction with any model.
Why this one:
Runtime.enable leak, the persona (UA, Client Hints, WebGL, timezone, locale) is coherent, and mouse and keyboard input are human-like. solveTurnstile() handles Cloudflare's checkbox.find(), markdown() and snapshot() all reach into closed shadow roots and cross-origin iframes, which Playwright's snapshot and Readability-style extractors miss.{{SECRET}} placeholders so the model never sees them, an allow-list restricts domains, and page content is fenced as untrusted data.generateExtractor() has the model write CSS selectors once. After that run() extracts with no LLM, and runOrHeal() regenerates the selectors when the site changes.With the right setup — a clean residential/mobile IP, plus a real GPU (EC2 g4dn/g5) for render-hash targets — browser-scraper is built to clear the fingerprint suites and anti-bot stacks that block headless automation:
| Detection / fingerprint suite | Anti-bot / WAF vendor | ||
|---|---|---|---|
bot.sannysoft.com — 0 failures | ✅ | Cloudflare (Turnstile) | ✅ |
| CreepJS — 0% headless, 0% stealth | ✅ | DataDome | ✅ |
bot-detector.rebrowser.net | ✅ | Kasada | ✅ |
| Pixelscan | ✅ | Akamai Bot Manager | ✅ |
| IPHey | ✅ | PerimeterX / HUMAN | ✅ |
| Browserscan | ✅ | Imperva (Incapsula) | ✅ |
| Incolumitas | ✅ | Shape / F5 | ✅ |
| Fingerprint.com | ✅ | AWS WAF Bot Control | ✅ |
A ✅ means the fingerprint + behavior layer passes — it is not a guaranteed bypass. Against hard targets your IP reputation is the ceiling: a datacenter ASN loses before the JavaScript runs, so route through a residential/mobile proxy (see The production stack).
browser-scraperis not a CAPTCHA solver — for reCAPTCHA v2 / hCaptcha / Arkose (FunCaptcha) image challenges, pair it with a solver service. It *does* keep reCAPTCHA v3 scores high via human-like input and warmed profiles.
Numbers were taken on a desktop Chrome. On a GPU-less Lambda running chrome-headless-shell (
@sparticuz/chromium) the surfaces differ — re-run the suites against your *actual* production binary and treat that as the source of truth (see Cloud deployment).
This is a precision tool, not a magic bypass — it's honest about its edges (see Notes & limitations), and that honesty is exactly what makes the green checks above worth anything.
scrape(), snapshot + refs, MCP server, CLI, LLM extractionnpm install @eurafaeldecarvalho/browser-scraper
or:
pnpm add @eurafaeldecarvalho/browser-scraper
Requires Node.js ≥ 20 and a local Chrome/Chromium (it's found automatically, or point at one with chromePath). For AWS Lambda, also install the optional @sparticuz/chromium — see Cloud deployment. Profile history seeding uses Node's built-in node:sqlite (Node ≥ 22.5) or the optional better-sqlite3; if neither is available it is simply skipped. The LLM helpers need ai (and zod if you use Zod schemas), and only if you import /ai.
import { Browser } from "@eurafaeldecarvalho/browser-scraper";
const browser = new Browser();
try { const tab = await browser.newTab(); await tab.goto({ url: "https://example.com" });
const heading = await tab.find({ selector: "h1" }); console.log(await heading?.text());
await tab.screenshot({ path: "example.png" }); } finally { await browser.close(); }
That's the whole shape of the library: a Browser, a Tab, and Elements you find and act on. Everything below is detail on top of these three.
const tab = await browser.newTab();
await tab.goto({ url: "https://shop.example.com/product/42" });
const { markdown, title, links, wordCount } = await tab.markdown({ mainContent: true, // drop nav/header/footer/cookie banners (default) query: "price shipping", // optional: keep only the relevant blocks (BM25), saves tokens links: "inline", // "inline" | "reference" | "none" includeIframes: false, // true = also inline iframe documents, cross-origin included });
const meta = await tab.metadata(); // { title, description, canonical, lang, image, openGraph, twitter, jsonLd: [...] } // JSON-LD often already has the price, rating and availability: check it before you prompt.
markdown() reads Chrome's own DOM tree over CDP (DOM.getDocument with pierce). No script is injected into the page, and the content of closed shadow roots is included in reading order, with slots composed. For HTML you already have, htmlToMarkdown(html) and extractMetadata(html) do the same without a browser.
scrape(): one call, cheapest tier firstimport { Browser, scrape } from "@eurafaeldecarvalho/browser-scraper";
const browser = new Browser({ proxy: process.env.PROXY }); // reuse it across URLs const page = await scrape({ url, browser, formats: ["markdown", "metadata", "links", "html", "screenshot"], strategy: "auto", // http → browser → stealth (or pin one tier) http: { curlImpersonate: "curl_chrome131" }, // optional: real Chrome TLS for the http tier });
page.tier; // which tier produced the result page.attempts; // [{ tier: "http", ok: false, reason: "needs JavaScript (empty app shell)", ms: 4 }, …]
| Tier | What runs | Used when |
|---|---|---|
http | One request, no Chrome (Node fetch, or curl-impersonate for a genuine Chrome JA3/JA4) | Static pages, APIs |
browser | The stealth Chrome | The HTTP response was blocked (403/429/503), a challenge, or an empty JS app shell |
stealth | The same tab plus a behavioral warm-up and an interactive Turnstile solve | The browser still sees a challenge page |
A challenge page is never returned as content: if every tier is blocked, scrape() throws a ScrapeError that carries the attempts.
console.log(await tab.snapshot());
// - main // - heading "Sign in" [level=1] // - textbox "Email" [ref=e3] // - button "Continue" [ref=e4] // - Iframe [ref=e5] // - checkbox "Verify you are human" [ref=e6] ← cross-origin iframe, still addressable
await (await tab.byRef({ ref: "e3" })).type({ text: "me@example.com" }); // human-like typing await (await tab.byRef({ ref: "e4" })).click(); // human-like mouse
The accessibility tree is computed on the composed tree, so elements inside closed shadow roots appear and can be clicked. Pass { interactive: true } to get just the flat list of clickable or typeable elements.
claude mcp add browser-scraper -- npx -y @eurafaeldecarvalho/browser-scraper mcp
Or in any MCP client config (claude_desktop_config.json, .cursor/mcp.json, …):
{
"mcpServers": { "browser-scraper": { "command": "npx", "args": ["-y", "@eurafaeldecarvalho/browser-scraper", "mcp", "--allowed-domains", "example.com", "--secrets", "/path/to/.env"] } } }
Tools:
| Tool | What it does |
|---|---|
navigate | Opens a URL and returns the snapshot |
snapshot | Accessibility outline with [ref=…] |
click | Clicks an element by ref, with human-like input |
type | Types into an element by ref, with human-like input |
press_key | Presses a key |
go_back | Goes back in history |
wait | Waits a number of seconds |
| markdown | Ma
Only the beginning is shown; read the rest in the repo