프로토타입 · 미리 보기: 공식 레지스트리의 모든 서버를 담고 있으며 30분마다 동기화해요. 리뷰와 계정 기능은 다음 단계에서 열려요.
PopNx MCPAI를 쓰는 사람을 위한 MCP 서버 · 쉬운 말로 설명해요

Websearch

제작자: SK-DEV-AI버전 1.10.0i★ –i내 컴퓨터에서 실행
레지스트리 이름io.github.SK-DEV-AI/websearch

설치

개요

제작자가 쓴 설명(영어 원문)

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

PopNx MCP의 세 기둥

이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.

할 수 있는 일

이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.

  • 연결 방식: 내 컴퓨터에서 실행
  • 전송 방식: stdio
  • 카테고리: 웹 및 브라우저
  • 입력해야 할 값: GROQ_API_KEYS, TAVILY_KEYS, NV_KEY, SE_KEY, S2_KEY

설치

쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.

설치하기 전에

  • 기본 점검: 1개 중 1개 통과
  • 내 컴퓨터에서 내 사용자 계정의 권한(파일, 네트워크, 앱)으로 실행돼요.
  • 직접 입력할 값: GROQ_API_KEYS, TAVILY_KEYS, NV_KEY, SE_KEY, S2_KEY

비밀로 표시된 값은 내 계정의 열쇠예요. 절대 다른 사람과 공유하거나 채팅에 붙여 넣지 마세요.

필요한 것

  • PyPIPython의 uv 설치(uvx 명령어용)

어떤 앱을 쓰세요?

위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.

Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요

{
  "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"
      }
    }
  }
}

터미널에서 이 명령어를 실행하세요

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

실행하기 전에 빈 값을 채워 주세요.

Cursor에서 열기

또는 설정을 직접 복사하기

프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요

{
  "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"
      }
    }
  }
}

브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.

VS Code에서 열기

또는 설정을 직접 복사하기

프로젝트의 .vscode/mcp.json에 붙여 넣으세요

{
  "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"
      }
    }
  }
}

브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.

이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.

선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.

직접 입력할 값

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

이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.

할 수 있는 일

내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.

기본 점검i

누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 6일 점검

  • ✓ 통과

    제작자와 저장소 일치

    레지스트리 이름이 GitHub 계정 SK-DEV-AI 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요

  • … 아직 점검 안 함

    계속 관리되고 있음

    아직 GitHub에서 이 저장소를 읽어 오지 않았어요

  • … 아직 점검 안 함

    라이선스 있음

    아직 GitHub에서 이 저장소를 읽어 오지 않았어요

  • – 해당 없음

    엔드포인트 응답

    내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요

  • – 해당 없음

    OAuth로 로그인

    내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요

  • … 아직 점검 안 함

    도구 설명에 숨겨진 지시 없음

    내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요

웹 및 브라우저 카테고리의 다른 서버와 비교i

  • 이 카테고리의 다른 서버 875개 중 0%보다 스타가 많아요
  • 이 카테고리의 다른 서버 875개 중 73%보다 최근에 레지스트리에 공개됐어요
  • 기본 점검 결과가 이 카테고리의 다른 서버 875개 중 100%와 같거나 더 좋아요

레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.

자주 묻는 질문

Websearch, 안전한가요?

해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.

어떤 키나 코드가 필요한가요?

입력해야 할 값: GROQ_API_KEYS, TAVILY_KEYS, NV_KEY, SE_KEY, S2_KEY

내 컴퓨터에서 실행되나요, 클라우드에서 실행되나요?

내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).

아직 관리되고 있나요?

GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(1.10.0)은 12일 전 레지스트리에 올라왔어요.

어떤 앱에서 쓸 수 있나요?

Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Python (uv)도 있어야 해요.

대신 쓸 수 있는 건 뭐가 있나요?

같은 카테고리에는: Browser Use, Chrome DevTools MCP, MCP Server Browser

대안

같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.

카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i

Browser Use

제작자: browser-use

Browser agents and stealth cloud browsers for AI: run web tasks, fill forms, extract data.

컴퓨터 또는 클라우드★ 120,087MIT16일 전 업데이트
설치

Chrome DevTools MCP

제작자: ChromeDevTools

MCP server for Chrome DevTools

내 컴퓨터에서 실행★ 54,821Apache-2.015일 전 업데이트
설치

MCP Server Browser

제작자: bytedance

MCP server for browser use access

내 컴퓨터에서 실행★ 39,550Apache-2.014개월 전 업데이트
설치

제작자의 README

README 열기

제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.

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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