Browser Use
Browser agents and stealth cloud browsers for AI: run web tasks, fill forms, extract data.
Descripción del creador (original en inglés)
Plain-English browser tests for AI agents: real Chrome, deterministic verdicts. Free, no API keys.
Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.
Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.
Elige la app de IA que usas y copia la configuración.
ANTHROPIC_API_KEYLos valores marcados como secretos son llaves de tu cuenta. Nunca los compartas ni los pegues en un chat.
Necesitas
¿Qué app usas?
Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.
Abre Claude Desktop → Settings → Developer → Edit Config y pega esto en claude_desktop_config.json
{
"mcpServers": {
"browserbash": {
"command": "npx",
"args": [
"-y",
"browserbash-cli"
],
"env": {
"ANTHROPIC_API_KEY": "your-value"
}
}
}
}Ejecuta esto en tu terminal
claude mcp add browserbash --env ANTHROPIC_API_KEY=your-value -- npx -y browserbash-cliCompleta los valores vacíos antes de ejecutarlo.
Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"browserbash": {
"command": "npx",
"args": [
"-y",
"browserbash-cli"
],
"env": {
"ANTHROPIC_API_KEY": "your-value"
}
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Pégalo en .vscode/mcp.json de tu proyecto
{
"servers": {
"browserbash": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"browserbash-cli"
],
"env": {
"ANTHROPIC_API_KEY": "your-value"
}
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Este se ejecuta en tu computadora, y ChatGPT solo puede conectarse a servidores en internet. Elige otra app.
Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.
Esta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.
Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.
Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 6 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub PramodDutta, dueña del repo
Todavía no hemos leído este repo en GitHub
Todavía no hemos leído este repo en GitHub
Este se ejecuta en tu computadora; no hay endpoint en internet
Se ejecuta en tu computadora y usa ajustes locales en su lugar
Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet
Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.
Superó 1 de 1 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.
Debes completar: ANTHROPIC_API_KEY
Se ejecuta en tu computadora. Tu app de IA lo inicia cuando hace falta, y los datos no pasan por los servidores del creador (a menos que el propio servidor llame a un servicio en línea).
El repo de GitHub cambió por última vez –, y la última versión (1.5.1) llegó al registro hace 4 meses.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Node.js en tu computadora.
En la misma categoría: Browser Use, Chrome DevTools MCP, MCP Server Browser
Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.
Cómo leer una tarjeta:★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi
Browser agents and stealth cloud browsers for AI: run web tasks, fill forms, extract data.
MCP server for Chrome DevTools
MCP server for browser use access
Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.
Plain-English browser automation. No selectors. Free and open-source.
You write a plain-English objective. An AI agent drives a real Chrome browser step by step — no selectors, no scripts. Ollama-first, so it runs on free local models with no API keys and nothing ever leaves your machine.
npm install -g browserbash-cli
browserbash run "Open news.ycombinator.com and store the top story title as 'top_story'"
[Website](https://browserbash.com) · [Docs / Learn](https://browserbash.com/learn) · [Tutorials](https://browserbash.com/tutorials) · [npm](https://www.npmjs.com/package/browserbash-cli)
Both layers are swappable: the engine interprets the English, the provider runs the browser.
| Engine | What it is | License |
|---|---|---|
stagehand (default) | Stagehand — open-source AI browser automation framework by Browserbase. act/extract/observe/agent primitives, self-healing, supports Anthropic/OpenAI/Google models. | MIT |
builtin | In-repo Anthropic tool-use loop driving Playwright. Used automatically for grids Stagehand can't attach to (LambdaTest, BrowserStack). | Apache-2.0 |
| Provider | Where the browser runs | Engine | Auth |
|---|---|---|---|
local (default) | Chromium/Chrome on this machine | stagehand or builtin | none |
cdp | Any Chrome DevTools Protocol endpoint (your grid, docker, Playwright MCP-managed browser) | stagehand or builtin | none |
browserbase | Browserbase cloud browsers | stagehand only | BROWSERBASE_API_KEY / BROWSERBASE_PROJECT_ID |
lambdatest | LambdaTest / TestMu AI cloud grid | builtin (auto) | LT_USERNAME / LT_ACCESS_KEY |
browserstack | BrowserStack Automate cloud grid | builtin (auto) | BROWSERSTACK_USERNAME / BROWSERSTACK_ACCESS_KEY |
Default model is auto, resolved in this order:
ollama/ — free, open source, no keysANTHROPIC_API_KEY set → claude-opus-4-8OPENAI_API_KEY set → openai/gpt-4.1| Backend | Model flag | Needs |
|---|---|---|
| Ollama — local, free, OSS (preferred) | auto or ollama/ e.g. ollama/qwen3 | Ollama running; OLLAMA_BASE_URL to override http://localhost:11434/v1, OLLAMA_MODEL to pin auto-detection. Same flag works for any OpenAI-compatible server (vLLM, LM Studio, llama.cpp). |
| Anthropic | claude-opus-4-8 | ANTHROPIC_API_KEY |
| OpenAI / Google | openai/gpt-4.1, google/gemini-2.5-flash | provider key (Stagehand engine) |
| OpenRouter — hundreds of models, one key | openrouter/ / e.g. openrouter/anthropic/claude-sonnet-4-6, openrouter/meta-llama/llama-3.3-70b-instruct | OPENROUTER_API_KEY (https://openrouter.ai/keys); override endpoint with OPENROUTER_BASE_URL |
| Anthropic-compatible gateway | claude-* + ANTHROPIC_BASE_URL | builtin engine routes through any Anthropic-compatible endpoint (e.g. a LiteLLM proxy fronting local models) |
ollama pull qwen3 # or any tool-capable local model
browserbash run "Open https://example.com and store the heading as 'h1'"
Stagehand engine (MIT) + local Chromium + Ollama (MIT) — zero cloud cost, no API keys. Tip: small models (≤8B) are flaky on multi-step objectives; Qwen3 / Llama 3.3 70B class works best.
Note: cloud-grid providers (lambdatest, browserstack) use the builtin engine, which speaks the Anthropic API — pair them with ANTHROPIC_API_KEY or an ANTHROPIC_BASE_URL gateway.
npm install
npm run build npm link # exposes the browserbash command
Requires Node ≥ 18 and Google Chrome stable (for the local provider).
export ANTHROPIC_API_KEY=sk-ant-...
browserbash run "Open https://news.ycombinator.com and store the top story title as 'top_story'"
export BROWSERBASE_API_KEY=... BROWSERBASE_PROJECT_ID=... browserbash run "..." --provider browserbase
export LT_USERNAME=... LT_ACCESS_KEY=... browserbash run "..." --provider lambdatest --headless
browserbash run "..." --cdp-endpoint ws://localhost:9222/devtools/browser/
browserbash run "..." --engine builtin
--agent switches stdout to NDJSON — one JSON object per line, stable schema:
browserbash run "<objective>" --agent --headless --timeout 120
{"type":"step","step":1,"status":"passed","action":"navigate","remark":"...","cached":false}{"type":"run_end","status":"passed|failed|error|timeout","summary":"...","final_state":{...},"duration_ms":...,"provider":"local","cache":"hit|miss|off","tokens_in":...,"tokens_out":...,"test_url":"..."}Exit codes: 0 passed · 1 failed · 2 error · 3 timeout. cached, cache, tokens_in/tokens_out are additive fields (present when relevant), so existing consumers are unaffected.
Full agent integration guide: docs/agents.md.
BrowserBash is a validation layer for AI agents: your coding agent builds a feature, BrowserBash proves it works in a real browser. One line plugs it into any MCP host:
claude mcp add browserbash -- browserbash mcp # Claude Code
Tools exposed: run_objective (one plain-English objective), run_test_file (a *_test.md), run_suite (a folder, parallel). Each returns the structured verdict JSON: status, summary, final_state, assertions, cost_usd, duration_ms. A failed test is a successful validation, so the tool call succeeds and the agent reads the verdict. No extra dependencies, stdio only, nothing leaves your machine.
Every run is kept in a private on-disk store (~/.browserbash/runs, secrets masked, capped at 200). Two ways to see them:
Local dashboard — free, no account, fully local:
browserbash dashboard # serve http://localhost:4477 and open it
browserbash run "..." --record --dashboard # run, then open the dashboard on this run browserbash dashboard --clear # wipe the local store
Left panel lists your runs; the main pane shows the verdict, extracted values and the recording — with --record you get a screenshot plus a session video (stagehand engine, video needs ffmpeg, bundled) or a native Playwright trace you can open at trace.playwright.dev (builtin engine). Nothing leaves your machine.
Cloud dashboard — optional, opt-in per run: a hosted dashboard at browserbash.com/dashboard with run history across machines and shareable per-run pages.
browserbash connect --key bb_... # one-time, key from browserbash.com/dashboard
browserbash run "..." --record --upload # push THIS run (verdict + recording) to the cloud
Without --upload nothing is sent to the cloud. BrowserBash is free and open source; cloud runs are kept 15 days.
A green run records the actions it took. The next identical run replays them with zero model calls, and the agent only steps back in when the page actually changed. Steady-state suites run at close to script speed and cost.
browserbash testmd run ./checkout_test.md # run 1: records the journal
browserbash testmd run ./checkout_test.md # run 2: replays, no model browserbash testmd run ./checkout_test.md --no-cache # ignore the cache for this run browserbash testmd run ./checkout_test.md --refresh-cache # wipe this test's entry, re-record
run_end.cache reports hit / miss / off. On by default; config set cache.enabled false to disable, cache.dir to relocate (default .browserbash/cache, gitignored by init). Secrets never enter the cache: values arrive through the variables channel (Stagehand) or are re-templatized to {{name}} tokens (builtin), and any cached action that types a secret is origin-pinned — replaying it on a different origin fails closed. Builtin journals are also HMAC-signed with a per-machine key (~/.browserbash/cache.key); an edited or foreign journal is ignored and simply re-recorded. CI fleets that want to share committed caches can set the same BROWSERBASH_CACHE_KEY (64 hex chars) on every runner.
run-all)Run a whole folder of *_test.md files at once with memory-aware scheduling:
browserbash run-all .browserbash/tests --concurrency 8 --junit out/junit.xml
min(requested, cpus, floor((mem - 2GB) / budget))), so big suites do not thrash the machine. Override with --concurrency, tune the estimate with --memory-budget . A hard watchdog also kills any test whose whole process tree (Node + Chromium) exceeds --memory-cap (default 2x the budget, 0 disables); the test is reported as an infra error with a test_kill event, and retried per --retries.Result.md; a failure never leaks state to the next test.--retries retries infra errors only (not real failures), --max-failures stops early, --stagger softens burst load.--events, add --agent to also stream on stdout), JUnit XML (--junit), and a RunAll-Result.md with a flaky column..browserbash/memory/history.json orders the next run (previously-failed first, then slowest first) and flags flaky tests. --no-memory opts out.--shard 2/4 runs a deterministic slice, computed on sorted discovery order so parallel CI machines agree without coordination.--matrix-viewport 1280x720,390x844 runs every test once per viewport; cells are labeled in events, JUnit and results. Single runs take --viewport WxH too.--budget-usd 2.50 (or --budget-tokens) stops launching new tests once estimated spend crosses the budget; the rest are reported skipped and the suite exits 2. Spend lands in RunAll-Result.md and JUnit .--notify POSTs the suite verdict when it ends (Slack URLs get Slack formatting).0 all passed · 1 any failed · 2 infra error or budget stop · 3 suite timeout.Plan on a strong model, execute on a cheap one, escalate back automatically after a failed step:
browserbash run "..." --model claude-opus-4-8 --model-exec claude-haiku-4-5
run_end reports tokens_in / tokens_out (builtin engine) so you can see what a run costs, plus a cost_usd estimate from a bundled per-model price table (override at ~/.browserbash/pricing.json; unknown models get no estimate rather than a wrong one). Set persistently with config set routing.executionModel .
*_test.md)Committable, reviewable Markdown tests:
# Login flow
Solo se muestra el principio; lee el resto en el repo