Browser Use
Browser agents and stealth cloud browsers for AI: run web tasks, fill forms, extract data.
Descripción del creador (original en inglés)
Multi-engine web search, fetch, browser control. 11 tools, keyless lanes.
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.
GROQ_API_KEYS, TAVILY_KEYS, NV_KEY, SE_KEY, S2_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": {
"websearch": {
"command": "uvx",
"args": [
"skdev-websearch-mcp"
],
"env": {
"GROQ_API_KEYS": "your-value",
"TAVILY_KEYS": "your-value",
"NV_KEY": "your-value",
"SE_KEY": "your-value",
"S2_KEY": "your-value"
}
}
}
}Ejecuta esto en tu terminal
claude mcp add websearch --env GROQ_API_KEYS=your-value --env TAVILY_KEYS=your-value --env NV_KEY=your-value --env SE_KEY=your-value --env S2_KEY=your-value -- uvx skdev-websearch-mcpCompleta los valores vacíos antes de ejecutarlo.
Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"websearch": {
"command": "uvx",
"args": [
"skdev-websearch-mcp"
],
"env": {
"GROQ_API_KEYS": "your-value",
"TAVILY_KEYS": "your-value",
"NV_KEY": "your-value",
"SE_KEY": "your-value",
"S2_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": {
"websearch": {
"type": "stdio",
"command": "uvx",
"args": [
"skdev-websearch-mcp"
],
"env": {
"GROQ_API_KEYS": "your-value",
"TAVILY_KEYS": "your-value",
"NV_KEY": "your-value",
"SE_KEY": "your-value",
"S2_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 SK-DEV-AI, 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: GROQ_API_KEYS, TAVILY_KEYS, NV_KEY, SE_KEY, S2_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 (1.10.0) llegó al registro hace 12 días.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Python (uv) 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.
mcp-name: io.github.SK-DEV-AI/websearch
Companion agent skills: SK-DEV-AI/skills · npx skills add SK-DEV-AI/skills
Multi-engine web search + fetch MCP server. Parallel fan-out across DuckDuckGo, Bing Web/News RSS, Tavily, Wikipedia, arXiv, Google News RSS, Brave (last resort — rate-limited from some networks), Google AI Mode, and intent-gated vertical lanes (MDN, Stack Exchange, GitHub, HN, Semantic Scholar, OSV vuln, grep.app/Sourcegraph code, GDELT news) — with consensus-merge dedup, a local cross-encoder reranker, and Groq synthesis with grounding checks.
depth defaults to 3 when a model lane is configured (more independent sources; measured) and 1 otherwise. Depth also sets how many pages are fetched: max(5, depth*2), ceiling 8. synthesize returns a short, cited answer that never invents: it says which source backs each claim, surfaces disagreement instead of averaging it, and marks itself truncated when it ran out of budget.offset). Optional distill (see below). For structured JSON use extract.fetch for one.stop_reason so you know whether the site was exhausted or a cap stopped it. Use for "read this whole docs site".javascript:/mailto:, dedups. Use before crawl or to find a "next" button.tables_found so you can pick one.dest_dir and refuses path traversal. Marks truncated if the byte cap stopped the transfer.had_previous: false.fetch. Pass session_id to reuse a persistent tab.browser_action call gets a fresh tab and closes it, so logins and cookies cannot survive. See below.effect (navigated / content_changed / none) so a submit that silently did nothing is visible rather than assumed.stop_reason.papers).Every one of these exists because an agent otherwise writes a one-off script:
| The task | The tool |
|---|---|
| Fetch 20 URLs | fetch_many |
| Read a whole docs site | crawl |
| Get every link on a page | extract_links |
| Pull a pricing table into CSV | extract_table |
| Save a PDF and get its path | download |
| "Did this page change?" | diff_page |
| Log in, then act across several calls | browser_session + browser_action(session_id=...) |
| Fill and submit a form | form_fill_submit |
| Walk "next" through pages | paginate |
browser_action opens one fresh tab per call and closes it afterwards. That is right for a single read, but it makes any interactive workflow impossible: no login, no cookies, no scroll position, no multi-step flow across calls.
A session is a named, long-lived tab:
browser_session(action="create", label="login", url="https://site.example/login")
browser_action(action="type", selector="#email", text="me@example.com", session_id="login-1a2b3c4d") browser_action(action="click", selector="#submit", session_id="login-1a2b3c4d") browser_action(action="text", session_id="login-1a2b3c4d") # same tab, still logged in browser_session(action="close", session_id="login-1a2b3c4d")
Sessions are opt-in: without session_id, behaviour is exactly as before. They are capped at 8 with least-recently-used eviction, tabs are always closed (including on eviction), and metadata is mirrored to ~/.cache/websearch/sessions.json so list can explain what survived a restart. Sessions need a browser, so they are local-only.
A fetched page can be 50k characters. The calling model pays for all of it even when it needed one fact. fetch(distill=true) runs a small model inside the tool first and returns a compressed result:
fetch(url="https://example.com/long-report", distill=True,
distill_question="What are the pricing tiers?")
The result never pretends to be the page:
| Field | Meaning |
|---|---|
distill.distilled | whether a summary was produced |
distill.raw_chars | size of the original text |
distill.grounded | whether every number and quoted span was found in the source |
distill.grounding.numbers_unverified | figures in the summary that do not appear in the source |
distill.grounding.quotes_unverified | quoted spans that are not verbatim |
distill.how_to_get_raw | how to get the untouched text: distill=false |
Below the size threshold (default 4000 chars) distillation is skipped and the raw text is returned, because a summary would cost more than it saves. On any failure the raw text is returned with distill_skipped explaining why - a broken summary is never returned in place of the page.
| Variable | Default | Meaning |
|---|---|---|
DISTILL_BASE_URL | http://127.0.0.1:11435/v1 | any OpenAI-compatible endpoint |
DISTILL_MODEL | reflection/beam:free | model id |
DISTILL_API_KEY | none | bearer token; without it the lane stays off |
DISTILL_RETRIES | 3 | attempts per call (1-10) |
DISTILL_MAX_TOKENS | 3000 | initial completion budget |
DISTILL_MAX_TOKENS_CEILING | 12000 | ceiling when escalating after empty content |
DISTILL_TIMEOUT | 90 | seconds per request |
DISTILL_THRESHOLD_CHARS | 4000 | below this, skip distillation |
search does not just rank results; it writes the answer. That answer is generated from the retrieved text alone, under rules that exist to stop the three failure modes of a search summary:
| Failure | What the prompt does |
|---|---|
| Invention | Nothing from the model's own knowledge. A claim with no citable source is deleted, not softened. If the results do not answer the question, saying so is the correct answer. |
| Bias | Rank is not evidence. The prompt says so explicitly, caps how many sources can come from one domain, requires disagreement between sources to be reported rather than averaged into a number that appears in no source, corrects false premises in the question, and labels vendor claims as vendor claims. |
| Injection | Results are wrapped in and declared untrusted data. A page that says "ignore previous instructions" is data, not instruction; the model must exclude it and say it did. |
Concision is structural, not a wish: a sentence ceiling, an answer-first rule, and a named ban on filler phrasing ("it is important to note", "overall", ...).
Everything is verifiable rather than claimed:
prompt_version, so a quality change can be tied to a revision instead of guessed attemperature is 0, so the same sources give the same textfinish_reason and truncated are returned; a half sentence is labelled instead of looking like a complete thoughtdiversity reports the source mix and whether the per-domain cap had to relaxas_of reports the newest publication date among the sources, and undated sources are labelled "Published: not stated", so freshness is never impliedduplicates_removed counts syndicated copies collapsed before synthesis, and figures_unverified lists numbers the answer contains that appear in no cited source (deterministic, no model call)unusable_sources names the results that could not become evidence - a 404, an error page, or a page with under 400 chars of text - with the reason, and unreadable_sources counts the ones with no text at allfollow_ups and marks synthesis.round = 2. Bounded: once per call, only under a 75s budget, and follow_up=false disables itgrounded) re-reads the answer against the exact text the first pass saw and flags sentences no cited source supports. It is marked advisory because it is another model's opinion, not a proofAll 20 tools carry MCP annotations (readOnlyHint, destructiveHint, idempotentHint, openWorldHint) so a client can tell a read from an action: search and fetch are read-only, download writes a local file without being destructive, browser_session changes local browser state only, and browser_action / form_fill_submit are marked destructive because a click or a form submit can have an effect that cannot be undone from here.
MCP clients cut a tool call at their own timeout (jcode: 300 s) and report a bare Request timeout after 300s with no payload. Measured over one day on a single busy server: 314 calls, median 2.7 s, p90 123 s, max 225 s, and 33 hard client timeouts — the tail is the problem, not the median. So the server bounds its own work instead of hoping the client waits:
| Env | Default | Meaning |
|---|---|---|
WEBSEARCH_TOOL_DEADLINE | 240 | Seconds one tool call may run. Keep it under the client timeout. 0 disables the bound |
WEBSEARCH_MAX_CONCURRENT | 8 | Simultaneous tool calls. Extra callers wait, then get busy. 0 = unlimited |
| WEBSEARCH_QUEUE_WAIT | 20 | Seconds a call may wait for a free slot before being answere
Solo se muestra el principio; lee el resto en el repo