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Specularis Mcp Audit MCP Server

Developer ToolsLow Risk9.7MCP RegistryRemote
Free

Server data from the Official MCP Registry

Free AI visibility (GEO/AEO) audit: can ChatGPT, Claude and Perplexity find and cite your website?

About

Free AI visibility (GEO/AEO) audit: can ChatGPT, Claude and Perplexity find and cite your website?

Remote endpoints: streamable-http: https://specularis-mcp-audit-production.up.railway.app/mcp

Security Report

9.7
Low Risk9.7Low Risk

Valid MCP server (2 strong, 2 medium validity signals). 1 known CVE in dependencies Imported from the Official MCP Registry. 1 finding(s) downgraded by scanner intelligence.

Endpoint verified · Open access · 2 issues found

Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.

Permissions Found in Source Code

Found by scanning the linked source code. This listing connects to a hosted endpoint, so none of this runs on your machine: it describes what the server software does where it is hosted.

HTTP Network Access

Connects to external APIs or services over the internet.

env_vars

Applies to the server that hosts this plugin, not to your machine.

How to Connect

Remote Plugin

No local installation needed. Your AI client connects to the remote endpoint directly.

Add this to your MCP configuration to connect:

{
  "mcpServers": {
    "io-github-adevaarons-specularis-mcp-audit": {
      "url": "https://specularis-mcp-audit-production.up.railway.app/mcp"
    }
  }
}

Documentation

View on GitHub

From the project's GitHub README.

Specularis AI Visibility Audit — MCP Server

Run a free AI visibility (GEO/AEO) audit on any website from inside Claude, ChatGPT, or any MCP client — check whether ChatGPT, Claude, Perplexity and Gemini can reach, read and cite it, and find the sources they cite instead.

Hosted endpoint (Streamable HTTP):

https://specularis-mcp-audit-production.up.railway.app/mcp

No installation needed — it's a remote MCP server. Add the URL above and you're done.

Connect it

Claude (claude.ai or Claude Desktop): Settings → Connectors → Add custom connector → paste the URL above.

Claude Code:

claude mcp add --transport http specularis-audit https://specularis-mcp-audit-production.up.railway.app/mcp

Then in any chat: "Audit example.com for AI visibility" — the tool runs.

Tools

ToolWhat it does
run_ai_visibility_audit(website_url, email?, name?, role?)Instant in-chat snapshot: AI crawler access (GPTBot, ClaudeBot, PerplexityBot, CCBot, Google-Extended), JSON-LD structured data, and llms.txt. Include an email to also receive the full scored report — 0–100 across six pillars — as a PDF. role accepts Real Estate Agent, Attorney, Founder or Other and tilts the scoring toward local entity signals, reviews and directories.
find_ai_citations(query, domain)Given a buyer question ("best personal injury lawyer in Miami") and a domain, returns the sources AI engines actually cite when answering it, tagged by engine, plus an appears in X of N count for the domain. The ranked source list is the off-site target list.
book_strategy_call()Returns a link to book a strategy call with Specularis.

Passing email to run_ai_visibility_audit sends a report and registers the person as a Specularis lead. Omit it for the snapshot alone.

Without an MCP client

The same scan engine is reachable over plain HTTP, with no key and no connector:

curl -s "https://specularis-mcp-audit-production.up.railway.app/api/scan?d=example.com"

Pass a bare hostname — no scheme, no path. It returns the full structured scan: per-bot fetch results, browser-vs-bot word counts for render-gap detection, parsed schema types, llms.txt, sitemap, and the six pillar scores. Useful for scanning domains in bulk.

If inconclusive is true, the scan could not complete — read inconclusiveReason and don't report a score.

What the full audit measures

Each bot is fetched with its real published user agent, so the result is what the engine itself would receive — not what a browser sees.

The report scores six pillars out of 100:

PillarMaxWhat it covers
access20Whether GPTBot, ClaudeBot and PerplexityBot can actually reach and receive the page
entity15Organization / Person / LocalBusiness schema, sameAs, address
content15Whether the text answers the questions buyers actually ask
offsite30The directories, review platforms and threads AI engines cite
freshness10Whether the content is maintained
technical10Sitemap, llms.txt, render gaps, crawlability

offsite is deliberately the largest pillar — more than access and entity combined. That reflects how the engines behave: they cite third-party corroboration far more often than a company's own marketing pages, so a technically flawless site can still be invisible.

A note on measuring "blocked". A real block is a 403, or a genuine interstitial with under 80 words of page text. Bot-protection layers return challenge pages intermittently, and counting those as blocks inflates the result — we published numbers once that were wrong for exactly this reason, and corrected them. Re-run before reporting a block.

Across 561 US businesses scanned in 2026, roughly half were effectively invisible to AI engines.

Use it as an agent skill

SKILL.md packages this as a portable agent skill in the open SKILL.md format — when to run an audit, how to read every field it returns, and the order to apply the fixes in. It works against either the MCP tools or the HTTP endpoint above.

Self-hosting

The server is a single-file Node app (Streamable HTTP transport).

npm install
npm start

Point any MCP client at http://localhost:3000/mcp.

VariablePurpose
N8N_WEBHOOK_URLBackend audit engine endpoint for the full PDF report
CONTACT_URLBooking link returned by book_strategy_call
AUDIT_URLWeb-form fallback link included in responses
PORTListen port (default 3000)
PERPLEXITY_API_KEYPrimary engine for find_ai_citations
ANTHROPIC_API_KEYAdds Claude as a second engine
GEMINI_API_KEYAdds Gemini as a third engine
OPENAI_API_KEYAdds ChatGPT as a fourth engine
OPENAI_MODELModel for the ChatGPT engine (default gpt-5-mini)
FINDER_DAY_MAXGlobal daily cap on citation-finder runs (default 250)

find_ai_citations needs at least one engine key. The engines array in each response reports which ones actually ran, so only claim the engines it names.

Who's behind it

Built by Specularis — a GEO/AEO agency helping businesses get found and cited by AI engines. The audit is free; the report is the real deliverable.

License

MIT

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