Ai Seo

io.github.AutomateLab-tech由 GitHub 帳號 AutomateLab-tech 發布v0.1.1更新於 Oct 24, 2026

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

概覽

AI 產生的概覽

本機 MCP 伺服器,用來稽核網頁在 AI 搜尋中的能見度:結構化資料、robots.txt、llms.txt、引用評分與 AEO/GEO 改寫。

可以做什麼
  • 對單一頁面與整個網站做 AI 引用就緒度稽核,提供八個面向的評分、依優先順序排列的問題與具體修正建議
  • 檢查抓取與索引訊號:AI 爬蟲的 robots.txt 規則、網站地圖、canonical、OpenGraph、hreflang 與 noindex
  • 驗證並產生 llms.txt,檢查現有檔案是否符合規格、連結是否失效
  • 評估引用價值、出現在 AI Overview 的機率、代理瀏覽就緒度,並模擬搜尋引擎是否會引用某個頁面
  • 擷取命名實體與 sameAs 連結,比較兩個網址,並依答案引擎與生成引擎最佳化改寫內容
  • 將稽核結果存成 Markdown 報告寫入磁碟
適用情境
適合有發布網頁內容、想了解 AI 助理與搜尋引擎為何引用或不引用自家頁面的情況,也適合在 CI 流程中做可重複的 AI-SEO 檢查。上線前驗證結構化資料、robots.txt 與 llms.txt 時同樣實用。
執行需求
透過 npx 以 stdio 在本機執行,需要 Node 20 或更新版本,不需 API 金鑰。若要對 JavaScript 渲染的網站做無頭渲染,需另外安裝 playwright-core 與 Chromium。儲存報告會在 MCP_WORKSPACE_ROOT 目錄下寫入檔案。
安裝前請注意
稽核會實際抓取目標網址,也就是從本機向這些頁面發出請求。改寫工具產生的新內容應在發布前人工檢視。儲存報告會在設定的工作區根目錄寫入檔案。v0.4.0 起工具名稱有變更,已儲存的呼叫方式可能需要更新。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Ai Seo,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

README

@automatelab/ai-seo-mcp

AI Citation Toolkit for the Model Context Protocol

[npm version] [license] [node]

Audit why AI systems do or do not cite your pages.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):

json
{  "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

bash
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):

json
{  "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:

bash
npm install playwright-corenpx 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.

yaml
- uses: actions/checkout@v4- name: AI-SEO audit  uses: AutomateLab-tech/[email protected]  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.

來源:README.md,提交 f42d4da

工具

0
SourceWeft 尚未在沙箱中啟動過該軟體包,因此其工具未知。

版本歷史

1
  1. v0.1.1最新Sep 16, 2026

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