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Websearch

作者:SK-DEV-AI版本 1.10.0i★ –i在你的电脑上运行
注册名称io.github.SK-DEV-AI/websearch

安装

概览

作者提供的说明(英文原文)

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

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 网页与浏览器
  • 你需要填写:GROQ_API_KEYS, TAVILY_KEYS, NV_KEY, SE_KEY, S2_KEY

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 需要你自己填写: GROQ_API_KEYS, TAVILY_KEYS, NV_KEY, SE_KEY, S2_KEY

标为机密的值是你账户的钥匙。千万不要分享给别人,也不要粘贴到聊天里。

你需要

  • PyPI已安装 Python 的 uv(用于 uvx 命令)

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 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"
      }
    }
  }
}

在终端中运行这条命令

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

运行前请先填写空着的值。

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.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"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "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"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上,无需账户。

需要你填写的值

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

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 SK-DEV-AI 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

与“网页与浏览器”中的其他服务器比较i

  • 星标数多于此分类中其他 879 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 879 个服务器的 73% 更新
  • 基础检查结果等于或优于此分类中其他 879 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

Websearch 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

你需要填写:GROQ_API_KEYS, TAVILY_KEYS, NV_KEY, SE_KEY, S2_KEY

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(1.10.0)于12天前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Python (uv)。

有什么可以替代它?

同一分类中有:Browser Use, Chrome DevTools MCP, MCP Server Browser

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Browser Use

作者:browser-use

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

电脑或云端★ 120,087MIT17天前更新
安装

Chrome DevTools MCP

作者:ChromeDevTools

MCP server for Chrome DevTools

在你的电脑上运行★ 54,821Apache-2.015天前更新
安装

MCP Server Browser

作者:bytedance

MCP server for browser use access

在你的电脑上运行★ 39,550Apache-2.014个月前更新
安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

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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