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)
Multi-engine web search, fetch, browser control. 11 tools, keyless lanes.
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.
GROQ_API_KEYS, TAVILY_KEYS, NV_KEY, SE_KEY, S2_KEYValues marked secret are keys to your account. Never share them or paste them into a chat.
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": {
"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"
}
}
}
}Run this in your 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-mcpFill in the empty values before running it.
Paste into .cursor/mcp.json in your project, or ~/.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"
}
}
}
}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": {
"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"
}
}
}
}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 6, 2026
The registry name was verified with the GitHub account SK-DEV-AI, 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.
You need to fill in: GROQ_API_KEYS, TAVILY_KEYS, NV_KEY, SE_KEY, S2_KEY
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 (1.10.0) reached the registry 12 days ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) 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.
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
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