io.github.cryptosun/proximens-oracle

Est-ce que io.github.cryptosun/proximens-oracle est sûr ?

Au dernier audit MCP Hub, le serveur MCP « io.github.cryptosun/proximens-oracle » est classé « Non encore testé ». Référencé dans l'annuaire. Seul le pentest comportemental fait foi, et il n'a pas encore été exécuté sur ce serveur. Le verdict est réévalué en continu ; consultez la fiche pour l'état à jour.

Méthode : MCP Hub analyse la description de chaque outil (couche 1) et, pour le verdict fort, exécute le serveur dans une micro-VM isolée avec leurres et réseau bloqué (couche 2). On publie des noms et des compteurs, jamais le contenu brut renvoyé par un outil.

Les 8 outils

• proximens_geo_audit_url≈ 1508 tokens

  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 in seconds — the default; "deep" = a full AI-synthesized consultancy report in Dutch with a 7-dimension scorecard and sector benchmark, takes ~30-50s), client_name (report header), branche_hint ("main:sub", e.g. "health_wellness:yoga_studio"), max_issues (1-25, default 10). RETURNS: JSON with a 0-100 score, severity-ranked issues (critical/major/minor) each with a finding and an actionable suggestion, top recommendations, and a markdown report; deep mode additionally returns score_set (7 GEO dimensions), sector (benchmark cohort), and a full consultancy-grade report_markdown (deep_mode="timeout_fallback" means the synthesis exceeded its budget and the fast result was returned instead). USE fast mode for quick checks and bulk triage; USE deep mode when you need a client-ready audit report. Free tier is blocked.

  Paramètres, retour & exemple (5)

  Paramètres

  • url · string · requis
    Target URL to audit
  • mode · string · optionnel · fast | deep
    fast = quick signal checks (seconds); deep = full AI-synthesized consultancy report with sector benchmark (~30-50s)
  • max_issues · integer · optionnel
    Maximum issues to return (default 10)
  • client_name · string · optionnel
    Optional client identifier for the audit report header
  • branche_hint · string · optionnel
    Branche hint in "main:sub" format, e.g. "health_wellness:yoga_studio". If omitted, principles are matched without branche filter.

  Exemple d'appel

  {"name": "proximens_geo_audit_url", "arguments": {"url": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"_wm": "texte", "url": "texte", "_meta": {}, "error": "texte", "score": 1, "sector": {}, "status": "complete", "signals": {}, "audit_id": "texte", "deep_mode": "ok", "score_set": {}, "recommendations": []}}

• proximens_geo_bulk_search≈ 698 tokens

  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), plus total_queries, total_matches and processing time. USE WHEN you need many lookups at once, e.g. a full-site audit or a keyword list, instead of repeated search_principles calls.

  Paramètres, retour & exemple (3)

  Paramètres

  • queries · array · requis
  • category · string · optionnel · technical | structured-data | content | ai-search | freshness | multimodal | user-signals | e-e-a-t
  • top_k_per_query · number · optionnel

  Exemple d'appel

  {"name": "proximens_geo_bulk_search", "arguments": {"queries": []}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"_meta": {}, "results": [], "total_matches": 1, "total_queries": 1}}

• proximens_geo_compare_urls≈ 788 tokens

  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 scoring as audit_url), the principles each page satisfies, the principles each page VIOLATES that the other satisfies (delta_principles), and strategic insights on where to close the gap. USE WHEN you want a competitive GEO gap analysis between your page and a rival's.

  Paramètres, retour & exemple (2)

  Paramètres

  • self_url · string · requis
    Your URL to audit
  • competitor_url · string · requis
    Competitor URL to compare against

  Exemple d'appel

  {"name": "proximens_geo_compare_urls", "arguments": {"self_url": "texte", "competitor_url": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"_meta": {}, "error": "texte", "insights": [], "self_url": "texte", "self_score": 1, "self_matched": [], "competitor_url": "texte", "competitor_score": 1, "delta_principles": {}, "competitor_matched": []}}

• proximens_geo_get_principle≈ 540 tokens

  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, evidence_count and the last-validated timestamp. USE WHEN you already have a principle id and need its full detail — typically to drill down after search_principles.

  Paramètres, retour & exemple (1)

  Paramètres

  • id · string · requis
    Principle UUID (from search_principles results)

  Exemple d'appel

  {"name": "proximens_geo_get_principle", "arguments": {"id": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"id": "texte", "_wm": "texte", "title": "texte", "summary": "texte", "branches": [], "category": "texte", "full_text": "texte", "confidence": 1, "similarity": 1, "source_url": "texte", "source_type": "texte", "upgrade_hint": "texte"}}

• proximens_geo_get_stats≈ 388 tokens

  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 timestamp. USE WHEN you need to gauge the size and quality of the corpus before relying on it.

  Paramètres, retour & exemple (0)

  Exemple d'appel

  {"name": "proximens_geo_get_stats", "arguments": {}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"tier_hint": "texte", "fetched_at": "texte", "total_evaluated": 1, "total_categories": 1, "total_principles": 1, "last_validated_at": "texte", "last_distillation_at": "texte", "confidence_distribution": {}}}

• proximens_geo_list_categories≈ 354 tokens

  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: technical, structured-data, ai-search, content, e-e-a-t, freshness, multimodal, user-signals, performance, query-intent, internal-linking, mobile, other. USE WHEN you want to discover which categories exist before narrowing a search_principles call with the category filter.

  Paramètres, retour & exemple (0)

  Exemple d'appel

  {"name": "proximens_geo_list_categories", "arguments": {}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"total": 1, "cached": true, "categories": []}}

• proximens_geo_search_principles≈ 758 tokens

  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 category (one of 13 GEO categories), top_k (1-25, default 10), min_confidence (0-1, default 0.5). RETURNS: ranked principles as JSON, each with id, title, summary, category, confidence and a relevance score; Pro/Enterprise tiers additionally return full_text and source. USE WHEN you need evidence-backed answers about how AI search engines (ChatGPT, Perplexity, Gemini, Google AI Overviews, Copilot) select, rank and cite web content.

  Paramètres, retour & exemple (4)

  Paramètres

  • query · string · requis
    Natural-language search query (e.g. "schema markup for local businesses" or "how to optimize for ChatGPT citations")
  • top_k · integer · optionnel
    Number of principles to return (max 25)
  • category · string · optionnel · technical | structured-data | content | ai-search | freshness | multimodal | user-signals | e-e-a-t
    Filter by category (one of 13 GEO categories)
  • min_confidence · number · optionnel
    Minimum confidence score (0-1). Default 0.5 filters noise; raise to 0.8+ for high-confidence claims only

  Exemple d'appel

  {"name": "proximens_geo_search_principles", "arguments": {"query": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"results": [], "tier_note": "texte", "query_used": "texte", "total_in_database": 1}}

• proximens_geo_synthesize_brief≈ 874 tokens

  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 with key points, the principles the content should address, and (Pro/Enterprise) FAQ suggestions and recommended schema.org markup. USE WHEN you need to brief a writer so a page is built to be cited by AI search engines.

  Paramètres, retour & exemple (4)

  Paramètres

  • topic · string · requis
  • target_branche · string · optionnel · local_services | digital_services | product_commerce | creative_professional | health_wellness | b2b_saas | universal
  • competitor_urls · array · optionnel
  • word_count_target · number · optionnel

  Exemple d'appel

  {"name": "proximens_geo_synthesize_brief", "arguments": {"topic": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"_meta": {}, "topic": "texte", "brief_id": "texte", "schema_markup": [], "faq_suggestions": [], "suggested_structure": {}, "estimated_word_count": 1, "principles_to_address": []}}

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Source

https://www.proximens.nl/mcp