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

AI SEO

作者:AutomateLab-tech版本 0.1.1i★ –i在你的电脑上运行
注册名称io.github.AutomateLab-tech/ai-seo

安装

概览

作者提供的说明(英文原文)

MCP server for AI-SEO auditing: schema, robots.txt, llms.txt, citation scoring, and AEO/GEO rewrites

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": {
    "ai-seo": {
      "command": "npx",
      "args": [
        "-y",
        "@automatelab/ai-seo-mcp"
      ]
    }
  }
}

在终端中运行这条命令

claude mcp add ai-seo -- npx -y @automatelab/ai-seo-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": {
    "ai-seo": {
      "command": "npx",
      "args": [
        "-y",
        "@automatelab/ai-seo-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": {
    "ai-seo": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@automatelab/ai-seo-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7日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 AutomateLab-tech 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 3563 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 3563 个服务器的 9% 更新
  • 基础检查结果等于或优于此分类中其他 3563 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

AI SEO 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(0.1.1)于6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★ 137MIT10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。

@automatelab/ai-seo-mcp

AI Citation Toolkit for the Model Context Protocol

Audit why AI systems do or do not cite your pages. MCP server. No API keys.

Works inside Claude, Cursor, Windsurf, Codex, and any MCP client that speaks stdio.


What it checks

  • AI crawler access - GPTBot, OAI-SearchBot, ClaudeBot, and PerplexityBot allowed or blocked in robots.txt
  • `llms.txt` - present, spec-compliant, links alive
  • Structured answer extraction - FAQ headings, BLUF paragraphs, answer-ready blocks
  • [[schema]] completeness - FAQPage, Article, Organization, Person; flags deprecated patterns
  • Entity clarity - named entity density and sameAs coverage that help AI systems identify the subject
  • Citation formatting - canonical URL hygiene, og:url, hreflang, noindex traps
  • Sitemap freshness - lastmod signals that tell crawlers the page is current

Run an audit. Get a list of citation-blockers, ranked.

You: Run an AI-SEO audit on https://automatelab.tech/launching-the-ai-seo-mcp/.

Result (truncated):

{

"url": "https://automatelab.tech/launching-the-ai-seo-mcp/", "score": 61, "grade": "C", "dimension_scores": { "schema": 45, "technical": 80, "structure": 40, "robots": 90, "freshness": 85, "authority": 40, "entity_density": 21, "sitemap": 100 }, "findings": [ { "severity": "critical", "category": "structure", "message": "No FAQ structure found (no FAQPage schema or H3 question headings).", "fix": "Add FAQ H3 headings ending in '?' with answer paragraphs, and a FAQPage JSON-LD block.", "estimated_impact": "high" }, { "severity": "warning", "category": "authority", "message": "Low authority signals - missing Organization or author Person schema.", "fix": "Add Organization JSON-LD and Article.author as a Person node with sameAs links.", "estimated_impact": "high" } ] }

Each finding names the exact fix. No opaque scores, no guesswork.


Install

npx -y @automatelab/ai-seo-mcp

Requires Node 20 or later.

Claude Desktop

Add to %APPDATA%\Claude\claude_desktop_config.json (Windows) or ~/Library/Application Support/Claude/claude_desktop_config.json (macOS):

{

"mcpServers": { "ai-seo": { "command": "npx", "args": ["-y", "@automatelab/ai-seo-mcp"] } } }

Restart Claude Desktop. Any MCP client that supports stdio transport works - same command / args pattern.

Optional: headless rendering for SPAs

By default audit_page reads raw HTML — fast, but misses content on React/Vue/Angular SPAs. Pass render: "headless" to spin up Chromium and audit the rendered DOM (adds 3-10s per audit).

One-time install:

npm install playwright-core

npx playwright install chromium

Then call audit_page with render: "headless". Use static for everything else — most marketing sites and docs render fine without it.


Run it in CI (GitHub Action)

This repo doubles as a GitHub Action. Drop it in a workflow to fail a PR when any page regresses below an AI-citation score - the same audit engine, gated on every change.

- uses: actions/checkout@v4
  • name: AI-SEO audit uses: AutomateLab-tech/ai-seo-mcp@v0.5.0 with: urls: "https://example.com,https://example.com/pricing" min-score: "70" # fail if any URL scores below this respect-robots: "true" # set false for staging / sites you own report-path: "ai-seo-report.md" # optional Markdown report artifact fail-on-regression: "true"

The Action builds the auditor from the pinned ref, runs audit_page on each URL, writes a scorecard to the job summary, and exits non-zero if any URL falls below min-score (when fail-on-regression is true). Outputs: min_score_observed, urls_audited, report_path. Full example: examples/github-action-usage.yml.


Further reading


MCP tool surface (20 tools)

ToolPurpose
audit_pageComposite AI-SEO audit with 8-dimension scoring (schema, technical, structure, robots, freshness, authority, entity density, sitemap).
audit_schemaValidate JSON-LD against Schema.org rules and AI-citation best practice. Flags deprecated patterns.
audit_canonicalCanonical link integrity, trailing-slash hygiene, og:url consistency.
audit_siteSingle-call site sweep: audit_page + check_robots + check_sitemap + audit_schema with overall grade and top-5 fixes.
audit_sitemapSite-wide content audit: stride-sample N URLs from the sitemap, run audit_page on each, return distribution + worst pages + top findings.
check_robotsParse robots.txt and report per-crawler allow/disallow for all known AI crawlers. Surfaces the GPTBot-blocked-but-OAI-SearchBot-allowed trap.
check_sitemapValidate XML sitemaps: presence, URL count, lastmod freshness, image/video extensions.
check_technicalHEAD tag audit: canonical, OpenGraph, Twitter Card, hreflang, HTTPS, noindex, title hygiene.
score_ai_overview_eligibilityScore a page's probability of appearing in Google AI Overviews using current correlation factors.
score_citation_worthinessScore how citable a page or text block is for Perplexity, ChatGPT, Google AI Overviews, and Claude. Includes per-section chunk_analysis / extractability_score: how cleanly an LLM can lift a standalone answer from each heading.
score_agentic_browsingScore a page against the Lighthouse "Agentic Browsing" category (May 2026): llms.txt, WebMCP, accessibility-tree integrity, and layout stability.
score_test_citationSimulate "would an AI engine cite this for this query?" via MCP sampling, with deterministic heuristic fallback.
llms_txt_generateGenerate llms.txt and optionally llms-full.txt from a domain's sitemap.
llms_txt_validateLint an existing llms.txt for spec compliance and broken links.
rewrite_aeoRewrite content for Answer Engine Optimization (BLUF structure, FAQ format, schema additions).
rewrite_geoRewrite content for Generative Engine Optimization (entity definitions, comparison tables, synthesis-ready structure).
extract_entitiesExtract named entities, sameAs links, and citation-density score from a page's content and structured data.
diff_pagesCompare two URLs for AI citation-worthiness: side-by-side dimension scores, gap analysis, and prioritized fix recommendations for url_a.
report_saveRender an audit_page / audit_site result as a Markdown report and write it to disk under MCP_WORKSPACE_ROOT.

v0.4.0 renamed tools from flat snake_case to dot-notation (audit_page, check_robots, …) for a navigable hierarchy. Update any saved invocations.

Environment variables: see ENV.md.


Contributing

Bug reports, feature ideas, and PRs welcome. See CONTRIBUTING.md.

Security

To report a vulnerability, see SECURITY.md.

License

MIT - see LICENSE.

Built by automatelab.tech

Maintenance and verification

See the maintenance guide for interpretation limits, current tool names where applicable, and reproducible verification.

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