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PopNx MCPMCP servers for people who use AI · explained in plain words

Websearch

by SK-DEV-AIversion 1.10.0i★ –iRuns on your computer
Registry nameio.github.SK-DEV-AI/websearch

Install

Overview

Description from the maker (original English)

Multi-engine web search, fetch, browser control. 11 tools, keyless lanes.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Web & browsers
  • You need to fill in: GROQ_API_KEYS, TAVILY_KEYS, NV_KEY, SE_KEY, S2_KEY

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • You fill in yourself: GROQ_API_KEYS, TAVILY_KEYS, NV_KEY, SE_KEY, S2_KEY

Values marked secret are keys to your account. Never share them or paste them into a chat.

You need

  • PyPIPython’s uv installed (for the uvx command)

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-mcp

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

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.

Open in VS Code

Or copy the settings yourself

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.

Values you fill in

  • GROQ_API_KEYS secret env
    Optional. Groq keys for synthesis and query rewriting.
  • TAVILY_KEYS secret env
    Optional. Tavily search lane.
  • NV_KEY secret env
    Optional. NVIDIA embeddings for ranking.
  • SE_KEY secret env
    Optional. Stack Exchange key (10k/day instead of 300).
  • S2_KEY secret env
    Optional. Semantic Scholar key (1 RPS).

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

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

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account SK-DEV-AI, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Web & browsersi

  • More stars than 0% of the other 878 servers in this category
  • Published to the registry more recently than 73% of the other 878 servers in this category
  • Basic checks equal to or better than 100% of the other 878 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Websearch safe?

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.

What keys or codes does it need?

You need to fill in: GROQ_API_KEYS, TAVILY_KEYS, NV_KEY, SE_KEY, S2_KEY

Does it run on my computer or in the cloud?

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).

Is it still maintained?

The GitHub repo last changed –, and the latest version (1.10.0) reached the registry 12 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: Browser Use, Chrome DevTools MCP, MCP Server Browser

Alternatives

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

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Install

README from the maker

Open the README

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.

websearch MCP Server

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.

Tools (20)

  • doctor — Run this first. Reports which lanes are usable right now and the exact command to enable the rest. Distinguishes "broken" from "needs optional setup". Never prints key values.
  • search — Open research questions. 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.
  • fetch — URL to markdown/text. Direct fetch with auto-fallback to a Chromium CDP browser for blocked/JS pages. PDF/EPUB/DOCX supported. Paginated (offset). Optional distill (see below). For structured JSON use extract.
  • fetch_many — Fetch several URLs in one call. Dedups, caps concurrency, honours robots.txt, shares the cache, returns per-URL success/status/content plus counts. Use when you have 2+ URLs; use fetch for one.
  • crawl — Breadth-first site crawl with hard caps (per-page cap, depth cap, robots.txt, dedup, concurrency). Returns each page plus a stop_reason so you know whether the site was exhausted or a cap stopped it. Use for "read this whole docs site".
  • extract_links — Every link on a page with anchor text, title and rel. Resolves relative hrefs, drops javascript:/mailto:, dedups. Use before crawl or to find a "next" button.
  • extract_table — HTML tables to json, csv or markdown, by selector and index. Reports tables_found so you can pick one.
  • download — Save a URL to disk; returns the local path, byte count, sha256 and content type. Writes only inside dest_dir and refuses path traversal. Marks truncated if the byte cap stopped the transfer.
  • diff_page — Has this page changed since it was cached? Returns changed/old_hash/new_hash plus added and removed lines. First call for a URL returns had_previous: false.
  • screenshot — ARIA accessibility snapshot (LLM-readable page text and interactive structure).
  • browser_action — Drive a real browser page (navigate, click, type, press a key, evaluate JS, read HTML/text, ARIA tree, screenshot). Use when a page needs interaction; for plain reading use fetch. Pass session_id to reuse a persistent tab.
  • browser_session — Create, list, inspect or close a persistent browser tab. Without one, every browser_action call gets a fresh tab and closes it, so logins and cookies cannot survive. See below.
  • form_fill_submit — Fill many fields, submit, and read the result in one call. Verifies each element exists, reads back each typed value, and refuses to submit if a value did not stick. Reports effect (navigated / content_changed / none) so a submit that silently did nothing is visible rather than assumed.
  • paginate — Click a "next" control, collecting a value per page, up to a cap. Stops honestly when the control is missing or has no effect, and reports stop_reason.
  • wikipedia — Full Wikipedia API client: articles, summaries, categories, links, pageviews, revisions, backlinks, geosearch, recent changes, random pages.
  • arxiv — arXiv paper search with boolean/phrase/wildcard query syntax (single-source; multi-source paper search lives in codesearch papers).
  • extract — Structured JSON from a page via CSS (fast, free), LLM, or regex strategies. Repeat calls cached.
  • pdf_extract — PDF to markdown/json/html. PyMuPDF fast path for text-layer PDFs, Docling+OCR fallback for scanned PDFs.
  • map_site — Survey a site's pages via sitemap XML (primary) + HTML link fallback, before fetching individually.
  • ping — Connectivity check for the internet and key search endpoints. Use before expensive calls when uncertain.

What replaced the throwaway scripts

Every one of these exists because an agent otherwise writes a one-off script:

The taskThe tool
Fetch 20 URLsfetch_many
Read a whole docs sitecrawl
Get every link on a pageextract_links
Pull a pricing table into CSVextract_table
Save a PDF and get its pathdownload
"Did this page change?"diff_page
Log in, then act across several callsbrowser_session + browser_action(session_id=...)
Fill and submit a formform_fill_submit
Walk "next" through pagespaginate

Persistent browser sessions

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")

-> {"session_id": "login-1a2b3c4d", ...}

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.

In-tool distillation (optional, off by default)

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:

FieldMeaning
distill.distilledwhether a summary was produced
distill.raw_charssize of the original text
distill.groundedwhether every number and quoted span was found in the source
distill.grounding.numbers_unverifiedfigures in the summary that do not appear in the source
distill.grounding.quotes_unverifiedquoted spans that are not verbatim
distill.how_to_get_rawhow 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.

VariableDefaultMeaning
DISTILL_BASE_URLhttp://127.0.0.1:11435/v1any OpenAI-compatible endpoint
DISTILL_MODELreflection/beam:freemodel id
DISTILL_API_KEYnonebearer token; without it the lane stays off
DISTILL_RETRIES3attempts per call (1-10)
DISTILL_MAX_TOKENS3000initial completion budget
DISTILL_MAX_TOKENS_CEILING12000ceiling when escalating after empty content
DISTILL_TIMEOUT90seconds per request
DISTILL_THRESHOLD_CHARS4000below this, skip distillation

The synthesis prompt (the answer you actually read)

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:

FailureWhat the prompt does
InventionNothing 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.
BiasRank 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.
InjectionResults 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:

  • the result carries prompt_version, so a quality change can be tied to a revision instead of guessed at
  • temperature is 0, so the same sources give the same text
  • finish_reason and truncated are returned; a half sentence is labelled instead of looking like a complete thought
  • diversity reports the source mix and whether the per-domain cap had to relax
  • as_of reports the newest publication date among the sources, and undated sources are labelled "Published: not stated", so freshness is never implied
  • duplicates_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 all
  • multi-hop: when the first answer admits a weakness (single source, a claim it could not tie to a source, or a stated gap), one extra round runs on the subquery that targets the gap. The response records follow_ups and marks synthesis.round = 2. Bounded: once per call, only under a 75s budget, and follow_up=false disables it
  • a second model pass (grounded) 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 proof
Tool annotations

All 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.

When a call takes too long (deadline, admission, partials)

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:

EnvDefaultMeaning
WEBSEARCH_TOOL_DEADLINE240Seconds one tool call may run. Keep it under the client timeout. 0 disables the bound
WEBSEARCH_MAX_CONCURRENT8Simultaneous 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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