Skip to main content

MCP server for technical SEO audits powered by the detail.web engine: site health score, issues across 8 categories and a GEO (AI-search visibility) sub-score.

Project description

atomno-mcp-seo-audit

PyPI Python License: MIT MCP

MCP (Model Context Protocol) server for technical SEO audits, powered by the detail.web engine. Run a site audit straight from your AI agent in Cursor, Claude Desktop or any MCP client — get a health score, issues across 8 categories, and a GEO (Generative Engine Optimization — visibility in AI search) sub-score.

Why not just ask an LLM to "analyze my site"?

Because a language model guesses — it can't read your TLS certificate's expiry date, measure response time, parse your sitemap.xml, or detect that GPTBot is blocked in robots.txt. Without tools it hallucinates from the URL; with browsing it eyeballs one rendered page. This server measures: real HTTP requests, security headers, redirect chains, structured-data validation — and returns a deterministic score (same site → same number), reproducible enough to put in a client report. Think of it as the instrument; the LLM is the analyst that interprets the readout. Best results come from the two together.

What you get

  • audit_site(url, depth=1, lang="ru") — one call returns:
    • health score 0–100 (higher is better) and a letter grade A–F;
    • issues grouped by category (security, SEO & indexing, performance, GEO, …), each with status pass / warn / fail;
    • a short human-readable summary.
  • audit_diff(url, lang="ru") — re-audits a site and compares it to the previous run: health/score delta and which checks got worse or better. The first call stores a baseline. This is something a one-off LLM question can't do — track a site over time. Stateful PRO feature (needs an API key).
  • list_checks(lang="ru") — the full catalogue of engine checks grouped by category, with a free / PRO badge on each — so you (and the agent) can see exactly what the free tier covers and what PRO unlocks.
  • explain_issue(check_id, lang="ru") — a deep-dive on a single check: why it matters and how to fix it. Pass a check_id from audit_site or list_checks. Title and category are localized; detailed advice is currently in Russian (the advice_lang field reports this).
  • validate_robots(content, lang="ru") — paste a robots.txt and get back syntax issues, whether a Sitemap: directive is present, whether CSS/JS is blocked from render bots, and which AI crawlers (GPTBot, ClaudeBot, …) are explicitly blocked. No fetch — validates the text you provide.
  • check_sitemap(url, lang="ru") — fetches a sitemap by URL and reports its format (urlset / sitemapindex), URL count and common problems (404, non-XML content type, http:// links, missing <lastmod>, the 50k-per-file limit). The fetch is SSRF-guarded on the server.
  • build_jsonld(type, fields, lang="ru") — generates a ready-to-paste schema.org JSON-LD <script> (Organization, LocalBusiness, Article, Product, FAQPage, BreadcrumbList, WebSite) and tells you which required/recommended fields are missing. It never invents data — only what you pass in.
  • build_meta(fields, lang="ru") — generates <head> meta tags (title, description, canonical, Open Graph, Twitter Card) and validates the title (50–60 chars) and description (120–160 chars) lengths.

Free vs PRO

Free (no key) PRO (with API key)
Checks core technical basics 40+ deeper checks (E-E-A-T, Schema.org, Goldmine title)
GEO 4 GEO signals GEO readiness sub-score + deep GEO checks
Crawl single page deep-crawl up to 20 pages (depth=2/3)

The audit engine itself stays on the server — this package is a thin client (HTTP calls + formatting only).

Install

uvx atomno-mcp-seo-audit

Or add to your MCP client config (mcp.json):

{
  "mcpServers": {
    "seo-audit": {
      "command": "uvx",
      "args": ["atomno-mcp-seo-audit"]
    }
  }
}

Configuration

All via environment variables:

Variable Default Purpose
DETAILWEB_API_BASE https://api.detailweb.ru Backend base URL
DETAILWEB_API_KEY PRO key (dwa_...). Without it → free tier
DETAILWEB_TIMEOUT 60 HTTP timeout (seconds)
DETAILWEB_LANG ru Default issue-title language (ru / en)

Get a PRO key in the detail.web dashboard → Account → API keys.

Example

"Audit https://example.com"

The agent calls audit_site("https://example.com") and gets back the health score, grade and the list of issues to fix.

License

MIT © atomno-labs. The open-source client talks to a proprietary hosted backend.


🇷🇺 На русском

MCP-сервер технического SEO-аудита на движке detail.web. Запускайте аудит прямо из ИИ-агента (Cursor, Claude Desktop и любой MCP-клиент): health-score, проблемы по 8 категориям и GEO-суб-балл (видимость в ИИ-поиске — ChatGPT, Perplexity, AI Overviews).

Чем отличается от «спросить нейросеть». Языковая модель гадает: она не прочитает срок вашего SSL-сертификата, не измерит время ответа, не распарсит sitemap.xml и не увидит, что GPTBot заблокирован в robots.txt. Этот сервер измеряет — настоящие HTTP-запросы, заголовки, редиректы, микроразметка — и даёт детерминированный score (тот же сайт → то же число), пригодный для отчёта клиенту. Это прибор; нейросеть — аналитик, который читает показания. Лучше всего работает связка.

Инструменты: audit_site (аудит + score + GEO), audit_diff (что изменилось с прошлой проверки — stateful PRO), list_checks (каталог проверок free/PRO), explain_issue (почему важно + как исправить), validate_robots, check_sitemap, build_jsonld, build_meta.

Установка:

uvx atomno-mcp-seo-audit

В конфиге MCP-клиента (mcp.json):

{
  "mcpServers": {
    "seo-audit": {
      "command": "uvx",
      "args": ["atomno-mcp-seo-audit"],
      "env": { "DETAILWEB_LANG": "ru" }
    }
  }
}

PRO-режим (40+ глубоких проверок, GEO-суб-балл, deep-crawl до 20 страниц): добавьте DETAILWEB_API_KEY (dwa_…) в env. Ключ — в кабинете detail.web → Аккаунт → API-ключи. Без ключа работает бесплатный тариф (базовые проверки, одна страница). Полное описание инструментов и настроек — в английской версии выше.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

atomno_mcp_seo_audit-0.4.0.tar.gz (21.4 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

atomno_mcp_seo_audit-0.4.0-py3-none-any.whl (19.0 kB view details)

Uploaded Python 3

File details

Details for the file atomno_mcp_seo_audit-0.4.0.tar.gz.

File metadata

  • Download URL: atomno_mcp_seo_audit-0.4.0.tar.gz
  • Upload date:
  • Size: 21.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.11.4

File hashes

Hashes for atomno_mcp_seo_audit-0.4.0.tar.gz
Algorithm Hash digest
SHA256 39724652038750c6c8a419c84b282cae1609c03920bed3710510ac0a228eb7c2
MD5 bd83f02d3522cc05a45a1133bf4ae4b8
BLAKE2b-256 3c52ffebac11e3a7de52990411da3057b2c00f9e3105122026c1c0815d21d657

See more details on using hashes here.

File details

Details for the file atomno_mcp_seo_audit-0.4.0-py3-none-any.whl.

File metadata

File hashes

Hashes for atomno_mcp_seo_audit-0.4.0-py3-none-any.whl
Algorithm Hash digest
SHA256 936d55d4014c5da5c64330026187dd768562f01f84c1ff09ff616ee3a5f630ae
MD5 3186167444cf2811886903d4b9599bd2
BLAKE2b-256 d2edeb1903582618f3b74277902b82f279eacfb8f8c85038816c3b09f711e010

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page