Which integrations are available for this server?

Integrates with Google PageSpeed Insights API to provide Core Web Vitals and Lighthouse performance opportunities for audited pages.

How do I use Seonix SEO MCP?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Seonix SEO MCP audit https://example.com and tell me the top SEO and speed problems with how to fix each." That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

Seonix SEO MCP

Official

by seonix-ai

Overview Schema Related Servers Score Discussions

TypeScript

Remote

Seonix SEO MCP

A free, open-source MCP server that lets any AI agent audit ANY website for SEO, GEO/AEO, and speed problems — and tell you how it should be.

Point Claude Desktop, Cursor, Cline, or any other MCP client at this server and ask it to "audit https://example.com and tell me the top SEO and speed problems with how to fix each." The agent crawls the site, runs the checks, and relays a plain-language report: what's wrong, why it matters, and the target state for each issue.

Platform-agnostic — works on any site: WordPress, Shopify, custom, static, anything reachable over HTTP. No CMS assumptions.
Read-only — it reports, it does not fix. The audit never modifies your site. It shows problems and gives CMS-neutral recommendations ("the page should have a unique <title> of 30–60 chars that includes the primary keyword"). Whether and how to fix is your decision.
Three pillars in one pass — SEO, GEO/AEO (AI-search visibility), and speed (Core Web Vitals + performance).
AI-agnostic — works with any MCP client. No vendor lock-in.
Free & open-source — MIT licensed.
Dependency-light — TypeScript, the official @modelcontextprotocol/sdk, and Node's built-in fetch. One runtime dependency.

The checks mirror the production Seonix scanner — same issue codes, severities, and thresholds — and every finding carries a recommendation ported from the Seonix remediation catalog, rewritten to be platform-neutral.

Note on WordPress auto-fixers. Earlier versions of this server shipped seven WordPress write tools (wp_update_content, wp_set_media_alt, wp_set_yoast_meta, …). They have been moved out of the tool surface into src/extras/wordpress-fixers.ts — kept for the record, but not part of the server. The auditor no longer needs any WordPress (or other) credentials to do its job.

What it does

The auditor discovers pages from sitemap.xml, fetches each page's HTML, and reports problems across three pillars. The AI client summarizes the structured result for you.

Tools

Tool	Auth	What it does
`audit_site`	none (read-only)	Audit a whole site for SEO + GEO/AEO + speed. Discovers pages via `sitemap.xml`, fetches each page, runs all checks, and returns a per-pillar summary plus a flat `issues[]` where every item carries a recommendation.
`speed_audit`	none (read-only)	Speed-only audit of one page. Always runs the HTML speed heuristics; with a PageSpeed key it also returns Core Web Vitals + the top Lighthouse opportunities.

Neither tool modifies anything.

What `audit_site` checks

SEO

Title — missing / > 60 / < 30 characters.
Meta description — missing / > 160 / < 50 characters.
Headings — missing H1 / multiple H1 / heading starts with an emoji / heading > 100 chars (likely a paragraph) / a heading before the first H1 / broken hierarchy (a skipped level).
Images — empty/missing alt (with the offending <img> snippet as evidence).
Mixed content — http:// resources on an https:// page.
Canonical — canonical URL mismatch.
Viewport — missing <meta name="viewport">.
Open Graph — missing OG tags / missing og:image.

GEO / AEO (AI-search visibility)

JSON-LD — Article author not a Person (resolves @id references so Yoast-style sites aren't false positives), datePublished missing, malformed or missing structured data.
AI-restrictive meta — page opts out of AI engines via nosnippet / noai / noimageai (meta robots or X-Robots-Tag).
/llms.txt — missing, or invalid (needs a # title + ≥ 1 Markdown link + ≥ 100 chars).
robots.txt — blocks AI crawlers (GPTBot, ClaudeBot, Google-Extended, PerplexityBot, OAI-SearchBot, anthropic-ai, ChatGPT-User, CCBot, Bytespider, Amazonbot, Applebot-Extended, meta-externalagent).

Speed

Always on (every fetched page, no key needed) — HTML heuristics:

Render-blocking <script> (no async/defer) and <link rel=stylesheet> in <head>.
<img> without width/height (layout-shift / CLS risk).
Below-the-fold <img> without loading="lazy".
Very large inline <style>/<script> blocks.
Heavy HTML document weight.
Excessive DOM node count.

When PAGESPEED_API_KEY is set — Google PageSpeed Insights (Lighthouse), on a small sample of pages:

Performance score + Core Web Vitals (LCP, CLS, INP, TBT, TTFB, FCP).
Top Lighthouse opportunities mapped to issue codes: render-blocking resources, unused CSS, unused JavaScript, properly-size / efficiently-encode / next-gen images, offscreen images, text compression, slow server response (TTFB), excessive main-thread work, large DOM, short cache lifetime. Severity is banded by estimated time savings, mirroring the Seonix scanner.

Output shape

audit_site returns:

{
  "site_url": "https://example.com",
  "pages_scanned": 25,
  "sitemap_source": "https://example.com/sitemap.xml",
  "speed": {
    "enabled_pagespeed": true,        // false when no PAGESPEED_API_KEY
    "pages_measured": 3,
    "measurements": [                  // one per PSI-sampled page
      { "url": "...", "strategy": "mobile", "performanceScore": 74,
        "lcpSeconds": 2.9, "cls": 0.04, "inpMs": 180, "tbtMs": 320, "ttfbMs": 410, "fcpSeconds": 1.8 }
    ]
  },
  "summary": {
    "seo":   { "score": 68, "health_label": "needs work", "issue_count": 8 },
    "aeo":   { "score": 94, "health_label": "good",        "issue_count": 3 },
    "speed": { "score": 82, "health_label": "good",        "issue_count": 7 }
  },
  "issue_count": 18,
  "issues_by_severity": { "error": 1, "warning": 9, "notice": 8 },
  "issues": [
    {
      "code": "title_too_long",
      "category": "seo",                       // "seo" | "aeo" | "speed"
      "severity": "warning",
      "url": "https://example.com/pricing",
      "evidence": { "length": 78, "title": "..." },
      "why": "Search engines typically display only about 60 characters of a title...",
      "target_state": "The <title> is 60 characters or fewer and leads with the important keywords.",
      "recommendation": "Shorten the <title> to 60 characters or fewer while keeping the primary keyword near the beginning..."
    }
    // ... every issue carries why / target_state / recommendation
  ]
}

health_label is good (score ≥ 80), needs work (≥ 50), or poor (< 50).
The speed pillar score is the median Lighthouse performance score across measured pages when PSI ran, otherwise a heuristic over the always-on speed checks.
Page discovery reads sitemap.xml (polite, ~1 request/second, default 25 pages, max 100) and fetches each URL. PSI is slow, so by default it only samples a few pages (homepage + up to 3 representative pages); the always-on HTML heuristics run on every fetched page.

Related MCP server: foglift-mcp

Install

Requires Node 18+ (uses global fetch).

git clone https://github.com/Effect-Agency/seonix-seo-mcp.git
cd seonix-seo-mcp
npm install
npm run build

This produces dist/index.js — the executable MCP server.

Configuration

The auditor needs no configuration — it works on any public site out of the box.

Variable	Required	Purpose
`PAGESPEED_API_KEY`	optional	A Google PageSpeed Insights API key. When set, `audit_site` and `speed_audit` add Core Web Vitals + Lighthouse opportunities (sampled). Without it, the speed pillar runs on always-on HTML heuristics only.

Getting a key takes a minute (enable the PageSpeed Insights API in a Google Cloud project and create an API key). It is free for typical audit volumes. PSI calls are slow (10–30s each), which is why the audit samples only a few pages by default — tune the sample with the speed_sample argument.

Add it to your AI client

Both clients launch the server with node dist/index.js. Use the absolute path to dist/index.js.

Claude Desktop

Edit claude_desktop_config.json (macOS: ~/Library/Application Support/Claude/claude_desktop_config.json):

{
  "mcpServers": {
    "seonix-seo": {
      "command": "node",
      "args": ["/absolute/path/to/seonix-seo-mcp/dist/index.js"],
      "env": {
        "PAGESPEED_API_KEY": "your-google-pagespeed-key"
      }
    }
  }
}

The env block is optional — omit it entirely to run with HTML speed heuristics only. Restart Claude Desktop after editing.

Cursor

Edit ~/.cursor/mcp.json (or Cursor Settings → MCP → Add new server):

{
  "mcpServers": {
    "seonix-seo": {
      "command": "node",
      "args": ["/absolute/path/to/seonix-seo-mcp/dist/index.js"],
      "env": {
        "PAGESPEED_API_KEY": "your-google-pagespeed-key"
      }
    }
  }
}

The same mcpServers shape works for Cline, Continue, and most other MCP clients.

Example prompts

Once connected, just talk to your agent:

"Audit https://example.com and tell me the top SEO and speed problems with how to fix each."
"Run a full audit of my site and give me the per-pillar health (SEO, AEO, speed) plus the 10 most severe issues."
"Check https://example.com for AI-search visibility — is anything blocking ChatGPT/Claude/Perplexity, and is the structured data in good shape?"
"Speed-audit my pricing page and explain the Core Web Vitals and what's hurting them."
"Crawl up to 50 pages of my site and list every page missing a meta description, with the recommended length."

A typical flow the agent runs on its own:

audit_site → gets the per-pillar summary + a flat list of issues, each with why / target_state / recommendation.
It groups the issues (by pillar, by severity, or by page) and explains the highest-impact ones in plain language.
You decide what to change — the MCP never touches your site.

How scoring works

SEO and AEO pillar scores start at 100 and subtract weighted demerits per issue (error > warning > notice), floored at 0. This is a transparent heuristic so an AI client can relay a single number to a human — it is not the exact dashboard algorithm.
Speed pillar score is the median Lighthouse performance score across the PSI-measured pages (the same basis Seonix uses for its speed pillar). When no PageSpeed key is configured, it falls back to the issue-based heuristic over the always-on speed checks.
Every issue still carries its own severity, so you can rank by severity regardless of the rolled-up scores.

Recommendations are platform-neutral

Recommendations live in src/recommendations.ts, ported from the Seonix remediation catalog but deliberately rewritten to be CMS-agnostic. You will never see "edit the Yoast field" or "change the WordPress block" — instead you get target states like "the page should have a unique <title> of 30–60 chars that includes the primary keyword" and imperative, vendor-neutral guidance that applies to any stack.

Development

npm run build     # compile TypeScript → dist/
npm start         # run the built server on stdio

src/audit.ts — all audit checks as pure, dependency-free functions over fetched HTML (SEO + AEO + speed heuristics) and the PageSpeed-Insights parsing/mapping. Easy to unit test.
src/recommendations.ts — the platform-neutral recommendation catalog (issue code → why / target_state / recommendation).
src/index.ts — the MCP server: ListTools + CallTool, sitemap discovery, page fetching, PSI sampling, and result assembly.
src/extras/wordpress-fixers.ts — the archived WordPress write tools. Not imported by the server; kept for the record.

Smoke test (JSON-RPC over stdio)

You can drive the server directly:

npm run build
# initialize → tools/list → tools/call audit_site, piped over stdin

(see the round-trip example in the project history — audit_site returns issues with recommendations and a speed section even without a PageSpeed key).

License

MIT. Free to use, modify, and distribute.

Install Server

license - permissive license

quality

maintenance

How are these scores calculated?

Maintenance

–Maintainers

–Response time

–Release cycle

–Releases (12mo)

Commit activity

Resources

GitHub Repository

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Seonix SEO MCP

What it does

Tools

What audit_site checks

Output shape

Install

Configuration

Add it to your AI client

Claude Desktop

Cursor

Example prompts

How scoring works

Recommendations are platform-neutral

Development

Smoke test (JSON-RPC over stdio)

License

Maintenance

Resources

Looking for Admin?

Tools

Latest Blog Posts

MCP directory API

What `audit_site` checks