# Proximens Oracle (remote · www.proximens.nl)

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

- Trust score: 70/100 (medium)
- Change this week: +4
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-08-03

## Components

- remote · `www.proximens.nl`: 70/100 (this document), [markdown](https://verifymcp.io/servers/cryptosun-proximens-oracle/www.md), [page](https://verifymcp.io/servers/cryptosun-proximens-oracle/www)

## Channel facts

- Endpoint: `https://www.proximens.nl/mcp`
- Transports: `streamable-http`
- Auth: `none`
- Version: `1.0.0`

## Trust breakdown

How this component scores in each security and reliability category. Every signal is checked automatically against the live server, and we only credit what we can confirm. Scores are 0–100 per category. Scoring method: https://verifymcp.io/docs/scoring (what has changed: https://verifymcp.io/docs/scoring/changelog)

Scored 2026-08-03.

- **Endpoint Security**: 83/100
  - The endpoint's TLS certificate is valid, in date, and uses a strong key.
  - No authorisation is required to call this server. Every tool declares its destructiveHint and none is destructive, so open access doesn't expose one.
  - HTTPS is enforced; there's no plaintext access path.
  - The HSTS (Strict-Transport-Security) header is present.
  - DNSSEC is configured correctly; the domain's records validate against the full chain to the root.
- **Transport & Reachability**: 100/100
  - Verified streamable-http transport via a live MCP handshake.
- **Schema Quality & AI Usability**: 66/100
  - AI-judged instruction clarity (excellent).
  - Context-footprint check failed: tool/resource definitions use about 1506 tokens (~188/item across 8 items; 8 tools + 0 resources), over budget; trim descriptions and params.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 0/100
  - Stability check failed: schema churn in the 8 days we've observed: 8 tool removals, 0 breaking changes, 0 auth/transport breaks, 8 additions.
- **Tool Coverage**: 89/100
  - 100% of tools have a non-trivial description (not blank, and not just the tool's name).
  - 63% of tool parameters carry a description.
  - Structured output schemas are declared (100% of tools); any adoption earns full credit.
- **Capabilities**: 100/100
  - Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.

## Install

### Claude

```bash
claude mcp add --transport http cryptosun-proximens-oracle https://www.proximens.nl/mcp
```

### Codex

```toml
[mcp_servers.cryptosun-proximens-oracle]
url = "https://www.proximens.nl/mcp"
```

### opencode

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "cryptosun-proximens-oracle": {
      "type": "remote",
      "url": "https://www.proximens.nl/mcp",
      "enabled": true
    }
  }
}
```

### OpenClaw

```bash
openclaw mcp add cryptosun-proximens-oracle --url https://www.proximens.nl/mcp --transport streamable-http
```

### Hermes

```yaml
mcp_servers:
  cryptosun-proximens-oracle:
    url: "https://www.proximens.nl/mcp"
```

### Other

```json
{
  "mcpServers": {
    "cryptosun-proximens-oracle": {
      "type": "http",
      "url": "https://www.proximens.nl/mcp"
    }
  }
}
```

The mcpServers block is a cross-client convention. Remote transports vary, so check your client's docs.

## Changelog

Every change recorded for this component, newest first. Days that predate change tracking, or that we cannot explain, say so: "we were watching and nothing happened" and "we were not watching" are different claims.

### 2026-07-31 (score 70, +4)

- [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server

### 2026-07-30 (score 66, 0)

- [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server

### 2026-07-27 (score 66, 0)

- [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server

### 2026-07-26 (score 66)

First indexed and scored.

## MCP tools (8)

### `proximens_geo_search_principles` (~290 tokens)

Search GEO principles (Proximens GEO Engine)

Semantic search over the Proximens GEO Engine: a curated, continuously-updated knowledge base of 3.000+ 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.

Input parameters:

- `category` (string): Filter by category (one of 13 GEO categories)
- `min_confidence` (number): Minimum confidence score (0-1). Default 0.5 filters noise; raise to 0.8+ for high-confidence claims only
- `query` (string, required): Natural-language search query (e.g. "schema markup for local businesses" or "how to optimize for ChatGPT citations")
- `top_k` (integer): Number of principles to return (max 25)

Output parameters:

- `query_used` (string)
- `results` (array)
- `tier_note` (string): Free-tier hint when top_k was capped
- `total_in_database` (integer)

### `proximens_geo_get_principle` (~127 tokens)

Get GEO principle by ID

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.

Input parameters:

- `id` (string, required): Principle UUID (from search_principles results)

Output parameters:

- `_wm` (string)
- `branches` (array)
- `category` (string)
- `confidence` (number)
- `evidence_count` (integer)
- `full_text` (string)
- `id` (string)
- `last_validated_at` (string|null)
- `similarity` (number|null)
- `source_diversity` (integer)
- `source_type` (string|null)
- `source_url`
- `summary` (string)
- `title` (string)
- `upgrade_hint` (string)

### `proximens_geo_list_categories` (~133 tokens)

List GEO principle 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: 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.

Output parameters:

- `cached` (boolean)
- `categories` (array)
- `total` (integer)

### `proximens_geo_get_stats` (~88 tokens)

Get GEO Engine statistics

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.

Output parameters:

- `confidence_distribution` (object)
- `fetched_at` (string)
- `last_distillation_at` (string|null)
- `last_validated_at` (string|null)
- `tier_hint` (string)
- `total_categories` (integer)
- `total_evaluated` (integer)
- `total_principles` (integer)

### `proximens_geo_audit_url` (~384 tokens)

Audit URL against Proximens GEO Engine

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.

Input parameters:

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

Output parameters:

- `_meta` (object)
- `_wm` (string)
- `audit_id` (string)
- `deep_mode` (string): Deep-mode outcome: ok = full synthesized report; timeout_fallback = synthesis exceeded budget, fast result returned
- `error` (string)
- `matched_principles` (array)
- `recommendations` (array)
- `report_markdown` (string)
- `score` (number)
- `score_set` (object): 7-dimension GEO scorecard (deep mode only)
- `sector` (object): Detected sector benchmark cohort (deep mode only)
- `signals` (object)
- `status` (string)
- `url` (string)

### `proximens_geo_compare_urls` (~161 tokens)

Compare URLs against Proximens GEO Engine

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.

Input parameters:

- `competitor_url` (string, required): Competitor URL to compare against
- `self_url` (string, required): Your URL to audit

Output parameters:

- `_meta` (object)
- `competitor_matched` (array)
- `competitor_score` (number)
- `competitor_url` (string)
- `delta_principles` (object)
- `error` (string)
- `insights` (array)
- `self_matched` (array)
- `self_score` (number)
- `self_url` (string)

### `proximens_geo_synthesize_brief` (~170 tokens)

Synthesize Content Brief from Proximens GEO Engine

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.

Input parameters:

- `competitor_urls` (array)
- `target_branche` (string)
- `topic` (string, required)
- `word_count_target` (number)

Output parameters:

- `_meta` (object)
- `brief_id` (string)
- `estimated_word_count` (number)
- `faq_suggestions` (array)
- `principles_to_address` (array)
- `schema_markup` (array)
- `suggested_structure` (object)
- `topic` (string)

### `proximens_geo_bulk_search` (~153 tokens)

Bulk Search Proximens GEO Engine

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.

Input parameters:

- `category` (string)
- `queries` (array, required)
- `top_k_per_query` (number)

Output parameters:

- `_meta` (object)
- `results` (array)
- `total_matches` (number)
- `total_queries` (number)

## Diagnostics

Captured diagnostic sections: TLS, DNSSEC, Authorisation, Transports. The full working is on the page: https://verifymcp.io/servers/cryptosun-proximens-oracle/www#diagnostics

## Score history

- 2026-08-03: 70
- 2026-08-02: 70
- 2026-08-01: 70
- 2026-07-31: 70
- 2026-07-30: 66
- 2026-07-29: 66
- 2026-07-28: 66
- 2026-07-27: 66
- 2026-07-26: 66

## Links

- Remote endpoint: https://www.proximens.nl/mcp
- Repository: https://github.com/cryptosun/Proximens
- Changelog RSS feed: https://verifymcp.io/servers/cryptosun-proximens-oracle/www/changelog.xml
- Changelog JSON feed: https://verifymcp.io/servers/cryptosun-proximens-oracle/www/changelog.json
- HTML version of this page: https://verifymcp.io/servers/cryptosun-proximens-oracle/www