原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
PopNx MCP为使用 AI 的人准备的 MCP 服务器 · 用大白话讲清楚

Wigolo

作者:KnockOutEZ版本 0.2.1i★ –i在你的电脑上运行
注册名称io.github.KnockOutEZ/wigolo

安装

概览

作者提供的说明(英文原文)

Local-first web intelligence MCP server for AI coding agents

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: 其他
  • 你需要填写:YOUR_API_KEY

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

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

  • npm已安装 Node.js(用于 npx 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": {
    "wigolo": {
      "command": "npx",
      "args": [
        "-y",
        "wigolo"
      ],
      "env": {
        "YOUR_API_KEY": "your-value"
      }
    }
  }
}

在终端中运行这条命令

claude mcp add wigolo --env YOUR_API_KEY=your-value -- npx -y wigolo

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": {
    "wigolo": {
      "command": "npx",
      "args": [
        "-y",
        "wigolo"
      ],
      "env": {
        "YOUR_API_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": {
    "wigolo": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "wigolo"
      ],
      "env": {
        "YOUR_API_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

  • YOUR_API_KEY 机密 必填 env
    Your API key for the service

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6日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 KnockOutEZ 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“其他”中的其他服务器比较i

  • 星标数多于此分类中其他 32464 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 32464 个服务器的 18% 更新
  • 基础检查结果等于或优于此分类中其他 32464 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

Wigolo 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:YOUR_API_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(0.2.1)于4个月前进入注册中心。

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 Node.js。

有什么可以替代它?

同一分类中有:Spec Driven Development, Remote Desktop Commander, yontu

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

Spec Driven Development

作者:formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

在你的电脑上运行★ 440MIT14个月前更新
安装

Remote Desktop Commander

作者:desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

在云端运行★ 211昨天更新
安装

yontu

作者:senrecep

Türkçe yazı denetimi: TDK kuralları, yapay zekâ izleri, metin türüne göre üslup.

在你的电脑上运行今天更新
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。

Local-first web intelligence for AI agents — no keys, no cloud, no metered bill.

works with Claude Code · Cursor · Codex · Gemini CLI · OpenCode · VS Code · Windsurf · Zed · Antigravity

and beyond LangChain · CrewAI · LlamaIndex · Vercel AI SDK · n8n & self-hosted agents · any MCP client · plain REST

sponsored by

Quickstart · Tools · Why wigolo · Discord · Sponsors · Benchmark · Docs · Examples · Licensing · Feedback · FAQ

Join the community on [Discord](https://discord.gg/BkUUgz2bNF) — questions, help, and what's being built next.

New features and updates ship steadily. Follow @yourtowhid on X for all of it and new ways to use wigolo, and reach out there for collaborations or feedback · also on LinkedIn


wigolo gives an AI agent one surface for everything web-related: search, fetch, crawl, extract, cache, find-similar, research, and autonomous gather loops. It runs wherever your agent runs — as an MCP server next to your coding agent, as a REST/MCP endpoint on the box where your self-hosted agents live, or embedded through an SDK inside your own app. The core tools need no API keys, nothing it touches leaves ~/.wigolo/, and no bill grows with how much your agent thinks.

Quickstart

npx wigolo init                              # set up the local engine — any system

npx wigolo init --agents=claude-code,cursor # …or set up + wire your day-to-day agents in one command

Requires Node ≥ 20 and ~1.5 GB of free disk on macOS, Linux, or Windows. Bare init sets up the local engine: it downloads the browser engine and on-device models, runs a health check, and reports each component. Adding --agents wires the named agents in the same run, so a coding agent you use daily is ready in one command.

  • Supported agents — --agents takes any of claude-code · cursor · codex · gemini-cli · opencode · vscode · windsurf · zed · antigravity (comma-separated); wigolo writes the MCP config and, where supported, instructions for each.
  • Any other setup — any MCP client, agent framework, or self-hosted agent registers npx -y wigolo in its own MCP config. The installation guide has the exact config block for every client, plus Docker, Homebrew, and single-file-binary channels.
  • More on the way — the supported list keeps growing, and a PR to add your agent is welcome; see CONTRIBUTING.md.
  • Interactive setup — --interactive is a plain-text flow; --wizard is the full terminal TUI.
  • Defer downloads — --no-warmup waits until first use. A failed component download never fails setup; init reports what's not ready with the exact fix and still completes.

init is unattended by default, so it's safe in scripts and CI, and any setup problem surfaces right here in the per-component report, before your agent's first call. Search, fetch, crawl, extract, cache, and find-similar work with no API key. Check it's healthy anytime:

npx wigolo doctor

To remove everything cleanly, run npx wigolo config --uninstall --yes. You can also paste the installation guide into any AI assistant and let it do the setup; it's written to be self-contained.

Recommended — a free key for research & agent

Search, fetch, crawl, extract, cache, and find-similar are fully keyless. research, agent, and search format=answer use an LLM to write the synthesized, cited answer. Without one they hand back a raw brief and evidence for your agent to assemble. A free Gemini key turns that into a finished answer:

export WIGOLO_LLM_PROVIDER=gemini

export GEMINI_API_KEY= # grab one at aistudio.google.com/apikey — the free tier is plenty

Any provider works (anthropic · openai · groq), or stay fully local and keyless with WIGOLO_LLM_PROVIDER=ollama (or any OpenAI-compatible URL). Set it in your shell or your agent's MCP env block. Providers, models, and the keyless local-model ladder are in the configuration guide.

What your agent gets back

Every search result is evidence the agent can act on. It carries a verbatim excerpt pinned to its exact position in the source, a citation ID the agent can quote, and a score it can inspect (abridged real shape):

{

"results": [{ "title": "Logical replication - PostgreSQL docs", "url": "https://www.postgresql.org/docs/current/logical-replication.html", "excerpt": "Logical replication is a method of replicating data objects…", "citation_id": "src-1", "source_span": { "start": 1042, "end": 1305 }, // byte-exact provenance "evidence_score": { "final": 0.86, "semantic": 0.91, "lexical": 0.78, "engine_consensus": 3 } }], "citations": [{ "id": "src-1", "url": "…" }], "freshness_signal": { "published": "2026-05-12", "confidence": "high" } }

Weak results get flagged as junk by wigolo's own scorer. Failed engines are reported and stale cache is labeled, so the agent always knows what it's standing on. Full response contracts per tool are in the tools reference.

Tools

ToolWhat it does
🔎 searchMulti-engine web search (18 direct adapters) with rank fusion, ML reranking, and an explainable per-result score. Pass a query array for parallel breadth. Scope by domain and time range, match an exact phrase, or return image results.
📄 fetchLoad one URL through a tiered router that auto-escalates from plain HTTP to a headless browser engine on anti-bot challenges or SPA shells. Clean markdown + metadata + links. Handles PDFs, a single-heading section, authenticated sessions, and page actions (click / type / scroll / screenshot).
🕸️ crawlMulti-page crawl — BFS, DFS, sitemap, or map-only. Per-domain rate limits, robots.txt respect, boilerplate dedup.
🧩 extractStructured data from a page: tables, metadata, JSON-LD, brand identity, named schemas (Article / Recipe / Product / …), or any custom JSON Schema.
💾 cacheQuery everything already seen — keyword or hybrid semantic. Plus stats, clear, and change detection.
🧲 find_similarPages similar to a URL or a concept, via 3-way fusion of keyword + semantic + live web.
🧠 researchDecompose a question → fan out sub-queries → fetch sources → synthesize a cited report (or a structured brief the host LLM writes from).
🤖 agentAutonomous gather loop: plan → search → fetch → extract → synthesize, with a step log, time budget, and optional output schema.
🔁 diff + ⏱️ watchSee exactly what changed on a page since last visit; re-check on demand and deliver changes to a webhook.

Every tool also runs from the terminal (wigolo search "…" --json), from an interactive shell with NDJSON piping (wigolo shell), over REST, and through the SDKs — CLI reference. Per-tool guides with the full parameter set are in docs/tools.md; runnable examples are in examples/.

Why it's different

wigolo isn't a free stand-in for the paid tools — it's built to match them. It's a focused web layer for your agents: an MCP and REST surface they call directly, with the search and extraction quality the paid services charge for. What separates it:

  • Built for agents. One MCP call fans out many queries across many engines in parallel, which a serial host tool-loop can't replicate. Every result carries transparent per-result scoring, and output is budget-aware.
  • Honest output. Stale cache, failed fetches, degraded backends, and truncation are surfaced in the result. When a bot-protected page can't be read, you get a labeled blocked_by_challenge failure, not a challenge shell returned as content.
  • $0 per query, free to re-query. Default search talks to public engines through direct adapters; the reranker and embeddings run on-device. Every response is cached, so asking again is instant and costs nothing.
  • Private by default. Cache, embeddings, models, and config live under ~/.wigolo/. Nothing reaches a third party unless you explicitly opt into an LLM for synthesis.

Here's what one real result looks like, dissected. It includes the failed engine and the weak result, because those are part of the answer too:

Benchmark

All four tools converged on the same core answer, and only one of them handed back verbatim, byte-pinned evidence while doing it.

One cold query ran live inside a single Claude Fable 5 session, fanned out to four web tools on equal footing (built-in WebSearch, wigolo, Tavily, Exa), and was judged by the agent on the evidence alone. All four converged on the same answer and the same top source, so the parity is demonstrated on-screen. wigolo alone returned verbatim excerpts pinned to byte-offset source spans, an explainable score d

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