Search / io.github.cryptosun/proximens-oracle
Proximens Oracle
R0· no sign-in1000+ Generative Engine Optimization (GEO) principles exposed via MCP for AI agents.
v1.0.0 · active · repository · descriptor JSON · versions
Search / io.github.cryptosun/proximens-oracle
R0· no sign-in1000+ Generative Engine Optimization (GEO) principles exposed via MCP for AI agents.
v1.0.0 · active · repository · descriptor JSON · versions
{
"mcpServers": {
"proximens-oracle": {
"type": "http",
"url": "https://www.proximens.nl/mcp",
"headers": {
"Authorization": "Bearer ${PROXIMENS_ORACLE_TOKEN}"
}
}
}
}claude mcp add --transport http proximens-oracle https://www.proximens.nl/mcp --header "Authorization: Bearer ${PROXIMENS_ORACLE_TOKEN}"[mcp_servers.proximens-oracle]
url = "https://www.proximens.nl/mcp"
bearer_token_env_var = "PROXIMENS_ORACLE_TOKEN"
{
"$schema": "https://opencode.ai/config.json",
"mcp": {
"proximens-oracle": {
"type": "remote",
"url": "https://www.proximens.nl/mcp",
"enabled": true,
"headers": {
"Authorization": "Bearer {env:PROXIMENS_ORACLE_TOKEN}"
}
}
}
}{
"mcpServers": {
"proximens-oracle": {
"type": "http",
"url": "https://www.proximens.nl/mcp",
"headers": {
"Authorization": "Bearer ${PROXIMENS_ORACLE_TOKEN}"
}
}
},
"deeplink": "cursor://anysphere.cursor-deeplink/mcp/install?name=proximens-oracle&config=eyJ0eXBlIjoiaHR0cCIsInVybCI6Imh0dHBzOi8vd3d3LnByb3hpbWVucy5ubC9tY3AiLCJoZWFkZXJzIjp7IkF1dGhvcml6YXRpb24iOiJCZWFyZXIgJHtQUk9YSU1FTlNfT1JBQ0xFX1RPS0VOfSJ9fQ%3D%3D"
}{
"servers": {
"proximens-oracle": {
"type": "http",
"url": "https://www.proximens.nl/mcp",
"headers": {
"Authorization": "Bearer ${PROXIMENS_ORACLE_TOKEN}"
}
}
}
}{
"mcpServers": {
"proximens-oracle": {
"httpUrl": "https://www.proximens.nl/mcp",
"headers": {
"Authorization": "Bearer ${PROXIMENS_ORACLE_TOKEN}"
}
}
}
}extensions:
"proximens-oracle":
enabled: true
name: "proximens-oracle"
type: streamable_http
uri: "https://www.proximens.nl/mcp"
headers:
"Authorization": "Bearer ${PROXIMENS_ORACLE_TOKEN}"
timeout: 300
Placeholders to fill from your own secret store: ${PROXIMENS_ORACLE_TOKEN}. The registry never accepts secret values.
protocol.modernnewest supported version is 2025-11-25; 2026-07-28 not supported, older versions are deprecated until 2027-07-28protocol.statelessonly applies to 2026-07-28 serversprotocol.transportstreamable HTTPprotocol.list_ttlonly applies to 2026-07-28 serversauth.prm, auth.as_metadata, auth.cimdno remote uses OAuthauth.secret_in_urlno templated URLtools.descriptionsevery tool has a descriptiontools.description_length1 tools have descriptions over 1,024 characters, which crowds the contexttools.schemasevery tool has an object input schematools.annotations8 of 8 tools declare readOnlyHint or destructiveHinttools.directory_hintsevery tool declares readOnlyHint, destructiveHint, idempotentHint and openWorldHinttools.token_costabout 2,343 tokens to load every tooltools.api_dumptools are not a one-to-one API dumpstability.changesno tool changes in 30 daysstability.rug_pullno tool changed its meaning under the same namedeps.known_vulns, deps.mcp_sdk_version, deps.resolvableno npm or PyPI packageNo tool definition changes recorded. A server's first observation is its baseline; later probes record what changes.
Checks run on what our credential-free, read-only probes observe; tools are never called and no code audit is performed. How it is computed.
+repository +namespace-matches-repo +reachable +uptime-100% ~updated-155d-ago
Derived from observable signals (official registry feed and our own credential-free probes); no code audit performed. How it is computed.
| remote | auth | reachable | uptime 30d | p50 | protocol | last ok |
|---|---|---|---|---|---|---|
https://www.proximens.nl/mcp streamable-http | none | yes | 100% | 509 ms | 2025-11-25 | 2026-10-20 |
proximens_geo_audit_urlread-only | 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. |
proximens_geo_bulk_searchread-only | 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. |
proximens_geo_compare_urlsread-only | 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. |
proximens_geo_get_principleread-only | 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. |
proximens_geo_get_statsread-only | 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. |
proximens_geo_list_categoriesread-only | 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. |
proximens_geo_search_principlesread-only | 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. |
proximens_geo_synthesize_briefread-only | 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. |
Schemas: list_tools.
{
"name": "io.github.cryptosun/proximens-oracle",
"title": "Proximens Oracle",
"$schema": "https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json",
"remotes": [
{
"url": "https://www.proximens.nl/mcp",
"type": "streamable-http",
"headers": [
{
"name": "Authorization",
"isSecret": true,
"description": "Bearer prx_live_* API key (Pro tier only — Free tier requires no auth)"
}
]
}
],
"version": "1.0.0",
"repository": {
"url": "https://github.com/cryptosun/Proximens",
"source": "github"
},
"description": "1000+ Generative Engine Optimization (GEO) principles exposed via MCP for AI agents."
}