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Aiseo Audit

agencyenterprise/aiseo-audit

Think Lighthouse for AI citations. This audits web pages across seven research-backed categories to measure how well ChatGPT, Claude, Perplexity, and Gemini can extract and cite your content. It runs 30+ checks covering entity extraction, readability, answer capsules, structured data, and authority signals. The scoring methodology comes from Princeton's GEO research on what generative engines actually quote. Use it in CI/CD with fail-under thresholds, track score changes over time with diff mode, or get instant feedback via the MCP integration. No API keys, no external calls beyond fetching the target URL. Output as terminal pretty-print, JSON, Markdown, or standalone HTML reports.

GitHub stars
8
tool
1
transport
STDIO
last updated
Aug 31, 2026
View on GitHub

Tools

1 tools

Public tool metadata for what this MCP can expose to an agent.

audit_urlThe included MCP server exposes an audit_url tool to Cursor, Claude Desktop, Windsurf, and other MCP clients, accepting optional queries and domain arguments.

The included MCP server exposes an audit_url tool to Cursor, Claude Desktop, Windsurf, and other MCP clients, accepting optional queries and domain arguments.

No parameter schema in public metadata yet.

Sponsors

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Readme

aiseo-audit

npm version License: MIT Node.js CI Coverage

A deterministic, Lighthouse-style audit for AI search readiness. Test how easily generative engines can fetch, extract, understand, and reuse a web page.

AI SEO measures content readiness, not traditional search rank. The score is a research-informed heuristic audit, not a citation probability or a promise that an engine will cite the page.

View the full README on GitHub

Details

Repository
github.com/agencyenterprise/aiseo-audit
Categories
Sales & Marketing, Search & Web Crawling, Automation & Workflows
Package
aiseo-audit-mcp
Transport
STDIO
Registry
MCP registry, active

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