Wigolo
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。
- 用户评价i暂无评价评价功能将在后续阶段与账户功能一起开放
- 我们的基础检查i2 项中通过 2 项依据公开信息检查;尚未扫描代码
- 使用情况i广泛使用↓ 1460/周 · ★ 5,535
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: 开发者工具
- 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
- 基础检查:2 项中通过 2 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:
YOUR_API_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
- 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。
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。
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 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10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
- ✓ 通过
仍在维护
代码最后更新于今天
- … 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“开发者工具”中的其他服务器比较i
- 星标数多于此分类中其他 5719 个服务器的 100%
- 发布到注册中心的时间比此分类中其他 5719 个服务器的 23% 更新
- 基础检查结果等于或优于此分类中其他 5719 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 2 项适用的基础检查中通过了 2 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 仓库最后更新于今天,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:REA, Netdata, Front-End Checklist
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:↓ 每周下载量i★ 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
Netdata
Real-time infrastructure monitoring with metrics, logs, alerts, and ML-based anomaly detection.
Front-End Checklist
Review frontend code and live pages against 386 quality-gated web development rules.
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 —
--agentstakes any ofclaude-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 wigoloin 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 —
--interactiveis a plain-text flow;--wizardis the full terminal TUI. - Defer downloads —
--no-warmupwaits 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
| Tool | What it does |
|---|---|
🔎 search | Multi-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. |
📄 fetch | Load 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). |
🕸️ crawl | Multi-page crawl — BFS, DFS, sitemap, or map-only. Per-domain rate limits, robots.txt respect, boilerplate dedup. |
🧩 extract | Structured data from a page: tables, metadata, JSON-LD, brand identity, named schemas (Article / Recipe / Product / …), or any custom JSON Schema. |
💾 cache | Query everything already seen — keyword or hybrid semantic. Plus stats, clear, and change detection. |
🧲 find_similar | Pages similar to a URL or a concept, via 3-way fusion of keyword + semantic + live web. |
🧠 research | Decompose a question → fan out sub-queries → fetch sources → synthesize a cited report (or a structured brief the host LLM writes from). |
🤖 agent | Autonomous gather loop: plan → search → fetch → extract → synthesize, with a step log, time budget, and optional output schema. |
🔁 diff + ⏱️ watch | See 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_challengefailure, 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