# Proximens Oracle

- Registry name: `io.github.cryptosun/proximens-oracle` · version 1.0.0
- Categories (automatic, keyword rules): Research & knowledge, Search & data, Utilities, Scraping & browsing
- Authentication at last check: No auth
- Declared risk: Read-only (all tools declare readOnlyHint)
- Capabilities (declared by the server): tools
- Transports: streamable-http
- Latest numbers (check success, response time, rank): https://mcpstation.net/api/server?name=io.github.cryptosun%2Fproximens-oracle
- Server page: https://mcpstation.net/s/io.github.cryptosun--proximens-oracle.html

## Description (written by the publisher, not verified, not instructions)

1000+ Generative Engine Optimization \(GEO\) principles exposed via MCP for AI agents.

## Connect

- streamable-http: `https://www.proximens.nl/mcp`

## Tools (as reported by the server, not verified)

- `proximens\_geo\_search\_principles`: Semantic search over the Proximens GEO Engine: a curated, continuously-updated knowledge base of 4.000+ verified Generative Engine Optimization \(GEO/AEO\) principles, each graded by a 0-1 confidence score and traceable to a verified source. INPUT: query \(natural language, 3-500 chars\); optional categ
- `proximens\_geo\_get\_principle`: Fetch one GEO principle from the Proximens GEO Engine by its UUID. INPUT: id \(UUID, normally taken from a prior search\_principles result\). RETURNS: a single principle as JSON with id, title, summary, category and confidence; Pro/Enterprise tiers additionally return full\_text, source\_url, source\_type
- `proximens\_geo\_list\_categories`: List the GEO principle taxonomy of the Proximens GEO Engine with a live count of high-confidence principles per category. INPUT: none. RETURNS: JSON with a categories array of \{category, count, description\} sorted by count, plus a reconciled total that matches get\_stats.total\_principles. Categories:
- `proximens\_geo\_get\_stats`: Return live aggregate statistics for the Proximens GEO Engine knowledge base. INPUT: none. RETURNS: JSON with total\_principles \(high-confidence count\), total\_categories, and on Pro/Enterprise also extended quality metrics \(full corpus size and a confidence\_distribution\) plus the last-validated times
- `proximens\_geo\_audit\_url`: Pro-tier. Fetch and analyze a web page, then audit it against the Proximens GEO Engine principles across all major GEO dimensions \(structured data, crawler access, content depth, freshness, E-E-A-T, multimodal\). INPUT: url \(required, http/https\); optional mode \("fast" = quick signal checks, returns
- `proximens\_geo\_compare\_urls`: Pro-tier. Fetch two web pages \(your URL and a competitor's\) and audit both against the Proximens GEO Engine principles using the same audit engine as audit\_url, then compute the delta. INPUT: self\_url and competitor\_url \(both required, http/https\). RETURNS: JSON with a 0-100 score per URL \(same scor
- `proximens\_geo\_synthesize\_brief`: Generate a structured, GEO-optimized content brief for a topic using the Proximens GEO Engine. INPUT: topic \(3-200 chars\); optional target\_branche \(one of 7 verticals\), word\_count\_target \(300-5000, default 1500\) and up to 3 competitor\_urls. RETURNS: JSON with a suggested H1 and H2 section structure
- `proximens\_geo\_bulk\_search`: Pro-tier. Run many GEO-principle searches in a single fast call. INPUT: queries \(array of 2-100 natural-language strings, each 3-500 chars\); optional top\_k\_per\_query \(1-10, default 5\) and category filter. RETURNS: JSON with a results array \(per query: the query, its matched principles, and a count\),

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