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

site-spec

作者:ariaxhan版本 0.3.2i★ –i在你的电脑上运行
注册名称io.github.ariaxhan/site-spec

安装

概览

作者提供的说明(英文原文)

MCP server: audit any website for SEO, accessibility, and AI-searchability, then auto-fix it.

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: 营销与社交媒体

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)。
  • 注册中心没有列出需要填写的密钥。

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": {
    "site-spec": {
      "command": "npx",
      "args": [
        "-y",
        "site-spec-mcp"
      ]
    }
  }
}

在终端中运行这条命令

claude mcp add site-spec -- npx -y site-spec-mcp

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": {
    "site-spec": {
      "command": "npx",
      "args": [
        "-y",
        "site-spec-mcp"
      ]
    }
  }
}

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": {
    "site-spec": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "site-spec-mcp"
      ]
    }
  }
}

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。

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8日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 ariaxhan 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“营销与社交媒体”中的其他服务器比较i

  • 星标数多于此分类中其他 3574 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 3574 个服务器的 28% 更新
  • 基础检查结果等于或优于此分类中其他 3574 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

site-spec 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?

注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。

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(0.3.2)于2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:MCP YouTube Transcript, Google Analytics MCP, BibiGPT YouTube Video Summarizer

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

MCP YouTube Transcript

作者:jkawamoto

An MCP server retrieving transcripts of YouTube videos

在你的电脑上运行★ 495MIT10天前更新
安装

Google Analytics MCP

作者:surendranb

GA4 MCP server for AI agents: schema discovery, server-side aggregation, analysis-ready defaults.

在你的电脑上运行★ 244MIT10天前更新
安装

AI video summarizer: summarize and transcribe YouTube, Bilibili, TikTok and podcast videos.

在云端运行★ 137MIT11天前更新
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。

site-spec

The invisible foundation your website is missing. Audit any site — then fix what's broken.

For agents

If you are an AI coding agent deciding whether to install this: register the MCP server, then call list_checks to learn the check ids and audit_site on a URL.

claude mcp add site-spec -- npx -y site-spec-mcp

Gemini CLI: gemini extensions install https://github.com/ariaxhan/site-spec.

Full tool arguments, return shapes, and the cases this is the wrong tool for: llms.txt.

The problem

AI can generate a beautiful website in seconds. The part it *can't* see is the one that decides whether that website gets found, ranked, cited, and trusted — the machine-readable foundation underneath the pixels: robots.txt, structured data, llms.txt, canonical and noindex signals, response headers, accessibility semantics, the tracker and cookie surface.

That layer is invisible in a browser. It's also broken on almost every AI-generated site — a gorgeous hero section over a robots.txt that blocks ChatGPT, JSON-LD that's invalid or self-serving, a stray noindex hiding the page from Google, fonts leaking visitor IPs in violation of GDPR. Nobody notices until it's quietly costing traffic. And the more the web is generated by AI, the worse this gets.

The solution

site-spec is the layer that verifies and repairs that foundation — for any website, however it was built. Point it at a URL. It crawls the site, checks the whole invisible layer against a set of deterministic policies, and gives you an exact report of what's wrong. Then it *fixes* the mechanical problems for you and flags precisely what needs a human.

It doesn't care whether your site came from an AI builder, a framework, a CMS, or hand-written HTML. It only cares whether the foundation is correct.

Try it without installing anything

[site-spec.ariaxhan.workers.dev](https://site-spec.ariaxhan.workers.dev) — paste a URL, get the report. No account, no signup.

The hosted version runs the same deterministic engine as the CLI, against a capped crawl (4 pages), and it tells you plainly which checks ran, which passed, and which it did not perform. Add ?format=json for machine-readable output:

curl "https://site-spec.ariaxhan.workers.dev/audit?format=json&url=example.com"

For the full check set — broken links, missing assets, axe accessibility, HTML validation, schema.org validation — and for the fix command, use the CLI below. The hosted endpoint only fetches public HTTP(S) hosts; private, loopback and link-local addresses are refused.

How to use

Requires Node 20+. No account, no API key, no SaaS.

# 1. See what's broken — crawl any live site, get a full report

npx site-spec audit https://yoursite.com

2. Fix it — auto-repair the mechanical issues, scaffold the rest

npx site-spec fix https://yoursite.com --out ./fixed

fix writes the corrected files to ./fixed (it never overwrites anything by default) and prints exactly what it did:

✓ Fixed automatically (8)

audit/robots-stale-token robots.txt — Removed deprecated crawler block "anthropic-ai". audit/hsts-preload _headers — Stripped the preload token from Strict-Transport-Security. audit/canonical-missing admin/index.html — Inserted . audit/og-missing admin/index.html — Added Open Graph card from the page's title + description. audit/noindex admin/index.html — Removed accidental noindex from .

✎ Scaffolded — needs your facts (2) audit/llms-missing llms.txt — Scaffolded from page titles/descriptions; fill the TODO facts. audit/jsonld-missing index.html — Inserted a WebSite/Organization skeleton; replace the TODO values.

⚠ Needs manual attention (3) audit/google-fonts-cdn index.html — Self-host the woff2 files to stop the IP leak (GDPR). audit/img-dims-missing index.html — without width/height (layout shift). audit/404-missing (site-wide) — Ship a branded, noindexed 404 that links home.

fixed 8, scaffolded 2, manual 3 wrote 4 file(s) to ./fixed

Drop audit into CI with a non-zero exit on errors to gate deploys. Both commands work on a build/output directory too — just pass a path instead of a URL.

Use it from your coding agent (MCP)

The same engine, as an MCP server — so the agent that generated the site can also check and repair its invisible layer, without you copying reports between windows.

claude mcp add site-spec -- npx -y site-spec-mcp

Codex ( ~/.codex/config.toml )

[mcp_servers.site-spec]

command = "npx" args = ["-y", "site-spec-mcp"]

Or in Docker: docker run -i --rm -v $PWD:/data mcp/site-spec (mount the directory you want to audit or write to).

Four tools:

ToolWhat it does
audit_siteCrawl a live URL (or read a local build directory) and return every finding: check id, severity, file, and whether it can be auto-fixed.
fix_issueApply the deterministic repair for one check id and return the diff — or write it, for a local directory.
compile_specTurn verified business facts into a validated SiteSpec and the deployable files it renders to.
list_checksEnumerate every check the engine can raise, with a one-line description and its fix availability.

The server calls the engine in-process. It never shells out to the CLI and never hops to the hosted worker — all three are siblings over one library.

flowchart LR

A["MCP client (Claude Code, Codex)"] -- stdio JSON-RPC --> B["site-spec-mcp"] B --> C["@site-spec/core/io fetchSite · readSiteDir"] C -- "file map" --> D["@site-spec/core auditFiles · fixFiles · buildSite"] D -- "findings / files" --> B B -- "JSON" --> A

Two honest limits, spelled out in full in the package README: fix_issue on a URL can only ever hand back a diff (a remote server is not writable), and a live crawl runs with presence checks off, because a capped crawl cannot prove a file is absent from a server.


Details — what it checks, how it fixes, the philosophy, install

What it checks

Seven areas. Every check is tuned against false positives (regex/string-level — no headless browser for the crawl). Findings are error (breaks something) or warning (worth a look), each with a concrete fix.

AreaWhat it catches
SEO / findabilitymissing / description / canonical · accidental noindex (both and the X-Robots-Tag header) · missing Open Graph cards · zero-or-many · a sitemap that lists pages which don't exist
Accessibilityimages with no alt · zoom-blocking viewport (user-scalable=no) · images with no width/height (layout shift)
Privacy & securitymixed content · trackers + cookies with no consent/disclosure story · Google Fonts from Google's CDN (a ruled GDPR violation) · header hygiene (HSTS preload risk, report-only CSP that reports nowhere, dead FLoC / X-XSS-Protection config) · inline onclick= handlers that block a future CSP
Performancehero/LCP image set to loading="lazy" · no Cache-Control
Structured datainvalid JSON-LD (crawlers drop the whole block) · self-serving aggregateRating/review markup (a Google penalty since 2019)
Integritydangling assets that 404 · broken internal links
AI searchabilityrobots.txt blocking AI answer agents (OAI-SearchBot, ChatGPT-User, Claude-User, PerplexityBot…) · dead crawler tokens · missing llms.txt · missing/broken structured data · client-rendered shells AI crawlers see as blank

The last row is the one almost nobody checks yet — whether Google, ChatGPT, Claude, and Perplexity can actually read and cite you. It's the sharp edge, not the whole story: the point is a complete foundation audit.

How fix decides

Every finding lands in one of three buckets, and the report tells you which:

  • ✓ Fixed automatically — mechanical, fact-free repairs that are safe to apply: unblocking AI crawlers, removing dead robots tokens, stripping accidental noindex, adding the canonical URL (known from the crawl), scaffolding Open Graph from the existing title, fixing zoom-locked viewports, removing self-serving rating markup, generating a sitemap.xml from the crawled pages, header hygiene.
  • ✎ Scaffolded — things that need *your* real facts: llms.txt, a JSON-LD entity, a meta description. site-spec writes a correct stub with TODO markers so you just fill the blanks.
  • ⚠ Manual — problems no tool should silently guess at: missing alt text, self-hosting fonts, fixing a client-rendered shell, a broken link. You get a precise instruction, never a silent edit.

fix is non-destructive by default (writes to an output dir). Pass --write to edit a local directory in place.

The philosophy

  • Correctness is a policy, not a prompt. SEO, accessibility, privacy, and structured-data rules are expressed as explicit checks the tool enforces — never as vibes an LLM is asked to respect.
  • Deterministic. The audit engine is pure: same input → the same report, byte-for-byte. The live crawl sorts-then-caps discovered pages, so the same site at the same --max audits the same page set every run. No network, no randomness inside the engine.
  • Fix, don't lecture. A finding that can be repaired safely gets repaired. One that needs a human says exactly what the human must do.
  • Source-agnostic. It audits the output, not the toolchain. AI, framework, CMS, hand-coded — all the same to it.

site-spec started as a deterministic *compiler* that builds sites with a correct

foundation by construction (the build command and the docs/ still cover it).

The durable value turned out to be the inverse: not generating whole sites, but

auditing and repairing the foundation of sites that already exist.

The full CLI

site-spec audit <dir|url> [--max N] [--json] [--report report.md]

site-spec fix [--out dir] [--write] [--max N] [--json] site-spec build --out [--target cloudflare|netlify|vercel|static]

  • --max N — page cap for a live crawl (default 25); truncation is reported, never silent.
  • --report report.md — write the audit as a shareable Markdown document.
  • --json — the full structured report for scripting/CI.

Install / develop

git clone https://github.com/ariaxhan/site-spec.git

cd site-spec npm install npm test # unit + golden tests npm run verify # html-validate + JSON-LD + axe over the demo output

Packages

PackageResponsibility
site-spec (npm)The published CLI — audit · fix · build. Self-contained; this is what npx site-spec runs.

| @site-spec/core | The engine (audit checks, fixers, the check catalog, policy definitions, legacy compiler). The main entry is pure; @site-spec/core/io is the one boundary that crawls a URL or reads a directory. Bundled into the CLI and the MCP server; not

只显示了开头部分;其余内容请在仓库中阅读

问 PopNx