mcp-crawl-parity

> Part of the GEO Stack research programme — where we discovered that Googlebot and AI crawlers make independent authority assessments on new domains.

An MCP (Model Context Protocol) server for analyzing Googlebot vs AI crawler parity from Nginx access logs and Google Search Console (GSC) data. Determines how consistently AI crawlers access your content relative to Googlebot.

npm install

Requires Node.js 18+.

npm start

Or directly:

node src/index.js

Parse an Nginx combined log format file and classify requests by crawler type.

Input:

• log_path (string, required): Path to Nginx access log file

Output:

{
  "googlebot_requests": 1234,
  "ai_crawler_requests": 456,
  "parity_ratio": 37.0,
  "parity_level": "low_parity",
  "paths_googlebot": 89,
  "paths_ai_crawler": 42,
  "unique_paths": 120
}

Cross-reference log analysis results with GSC search analytics data.

Input:

• logs_analysis (object, required): Output from analyze_logs or similar structure
• gsc_data (array, required): GSC analytics records with page, impressions, clicks, ctr, position

Output:

{
  "both": 45,
  "logs_only": 20,
  "gsc_only": 35,
  "total_analyzed": 100
}

Generate a comprehensive crawl parity report combining logs and GSC data.

Input:

• log_path (string, required): Path to Nginx access log file
• gsc_data (array, required): GSC analytics records

Output:

{
  "timestamp": "2026-03-26T14:30:00.000Z",
  "logs_analysis": { ... },
  "gsc_crossref": { ... },
  "summary": {
    "googlebot_activity": "detected",
    "ai_crawler_activity": "detected",
    "parity_status": "low_parity",
    "parity_percentage": 37.0,
    "recommendation": "Low parity - AI crawlers are significantly underrepresented"
  }
}