Proximens GEO Engine MCP

The Proximens GEO Engine is an MCP server that exposes Generative Engine Optimization (GEO) principles, allowing AI agents to optimize content for visibility in search engines and AI assistants like ChatGPT, Gemini, and Perplexity.

Endpoint and access

No sign-in to connect and list tools. Individual tools may still need a vendor account, credentials, or permissions; check the documented prerequisites.

Community listingStreamable HTTPNo sign-inEndpoint checked 2026-11-06Published by Proximens

MCP endpoint (Streamable HTTP)

https://www.proximens.nl/mcp

Vendor documentation

What its tools do

8 tools, grouped by the hints the server advertises. Hints are self-declared, not verified behavior.

8 of 8 have a description · 8 of 8 declare behavior hints · 4 of 6 with parameters document them all

Checks and signals

Each line is separate evidence, not a trust score.

Passed Endpoint answered the live check · Nov 6, 2026, 3:46 PM UTC
Availability 1 of 1 checks passed in 30 days

What you can do with it

Optimize website content for AI search visibility
Apply GEO principles to improve AI citation rates
Integrate GEO strategies into AI agent workflows

Source and maintenance

Community listingRegistry 1.0.0

mcp-registry: io.github.cryptosun/proximens-oracle@1.0.0 Source repository

Maintenance checked: Nov 6, 2026, 3:14 PM UTC

Protocol and capabilities

Server: proximens-geo-engine 0.1.0
MCP protocol negotiated in check: 2025-11-25
Tools: 8 advertised
Resources: Not advertised
Resource templates: Not advertised
Prompts: Not advertised

Server-advertised capabilities

{
  "tools": {
    "listChanged": false
  }
}

Tools

8 advertised

proximens_geo_search_principles — Search GEO principles (Proximens GEO Engine)

Advertised by the server during the last successful anonymous check.

Advertised read-only

Semantic search over the Proximens GEO Engine: a curated, continuously-updated knowledge base of 8.000+ Generative Engine Optimization (GEO/AEO) principles, each graded by a 0-1 confidence score and traceable to a source. INPUT: query (REQUIRED, natural language, 3-500 chars, e.g. "how does ChatGPT choose which FAQ to cite"); 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_search_principles input schema

{
  "type": "object",
  "required": [
    "query"
  ],
  "properties": {
    "query": {
      "type": "string",
      "maxLength": 500,
      "minLength": 3,
      "description": "Natural-language search query (e.g. \"schema markup for local businesses\" or \"how to optimize for ChatGPT citations\")"
    },
    "top_k": {
      "type": "integer",
      "default": 10,
      "maximum": 25,
      "minimum": 1,
      "description": "Number of principles to return (max 25)"
    },
    "category": {
      "enum": [
        "technical",
        "structured-data",
        "content",
        "ai-search",
        "freshness",
        "multimodal",
        "user-signals",
        "e-e-a-t",
        "mobile",
        "performance",
        "query-intent",
        "internal-linking",
        "other"
      ],
      "type": "string",
      "description": "Filter by category (one of 13 GEO categories)"
    },
    "min_confidence": {
      "type": "number",
      "default": 0.5,
      "maximum": 1,
      "minimum": 0,
      "description": "Minimum confidence score (0-1). Default 0.5 filters noise; raise to 0.8+ for high-confidence claims only"
    }
  },
  "additionalProperties": false
}

proximens_geo_search_principles output schema

{
  "type": "object",
  "required": [
    "results",
    "query_used",
    "total_in_database"
  ],
  "properties": {
    "results": {
      "type": "array",
      "items": {
        "type": "object",
        "required": [
          "id",
          "title",
          "summary",
          "category",
          "confidence"
        ],
        "properties": {
          "id": {
            "type": "string",
            "format": "uuid"
          },
          "_wm": {
            "type": "string"
          },
          "title": {
            "type": "string"
          },
          "summary": {
            "type": "string"
          },
          "category": {
            "type": "string"
          },
          "full_text": {
            "type": "string"
          },
          "confidence": {
            "type": "number",
            "maximum": 1,
            "minimum": 0
          },
          "similarity": {
            "type": "number",
            "maximum": 1,
            "minimum": 0,
            "description": "Relevance score for the query (0-1)"
          },
          "source_url": {
            "anyOf": [
              {
                "type": "string",
                "format": "uri"
              },
              {
                "type": "null"
              }
            ]
          },
          "source_type": {
            "type": [
              "string",
              "null"
            ]
          },
          "upgrade_hint": {
            "type": "string"
          },
          "evidence_count": {
            "type": "integer",
            "minimum": 0
          }
        },
        "additionalProperties": false
      }
    },
    "tier_note": {
      "type": "string",
      "description": "Free-tier hint when top_k was capped"
    },
    "query_used": {
      "type": "string"
    },
    "total_in_database": {
      "type": "integer",
      "minimum": 0
    }
  },
  "additionalProperties": false
}

proximens_geo_search_principles annotations

{
  "title": "Search GEO principles (Proximens GEO Engine)",
  "readOnlyHint": true,
  "openWorldHint": false,
  "idempotentHint": true,
  "destructiveHint": false
}

proximens_geo_get_principle — Get GEO principle by ID

Advertised by the server during the last successful anonymous check.

Advertised read-only

Fetch one GEO principle from the Proximens GEO Engine by its UUID. INPUT: id (REQUIRED, UUID string taken from a prior search_principles result — call search_principles first if you do not have one). 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_principle input schema

{
  "type": "object",
  "required": [
    "id"
  ],
  "properties": {
    "id": {
      "type": "string",
      "format": "uuid",
      "description": "Principle UUID (from search_principles results)"
    }
  },
  "additionalProperties": false
}

proximens_geo_get_principle output schema

{
  "type": "object",
  "required": [
    "id",
    "title",
    "summary",
    "category",
    "confidence"
  ],
  "properties": {
    "id": {
      "type": "string",
      "format": "uuid"
    },
    "_wm": {
      "type": "string"
    },
    "title": {
      "type": "string"
    },
    "summary": {
      "type": "string"
    },
    "branches": {
      "type": "array",
      "items": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "object",
            "required": [
              "main",
              "subs",
              "relevance"
            ],
            "properties": {
              "main": {
                "enum": [
                  "local_services",
                  "digital_services",
                  "product_commerce",
                  "creative_professional",
                  "health_wellness",
                  "b2b_saas",
                  "universal"
                ],
                "type": "string"
              },
              "subs": {
                "type": "array",
                "items": {
                  "type": "string"
                }
              },
              "relevance": {
                "type": "integer",
                "maximum": 3,
                "minimum": 0
              }
            },
            "additionalProperties": false
          }
        ]
      }
    },
    "category": {
      "type": "string"
    },
    "full_text": {
      "type": "string"
    },
    "confidence": {
      "type": "number",
      "maximum": 1,
      "minimum": 0
    },
    "similarity": {
      "type": [
        "number",
        "null"
      ]
    },
    "source_url": {
      "anyOf": [
        {
          "type": "string",
          "format": "uri"
        },
        {
          "type": "null"
        }
      ]
    },
    "source_type": {
      "type": [
        "string",
        "null"
      ]
    },
    "upgrade_hint": {
      "type": "string"
    },
    "evidence_count": {
      "type": "integer",
      "minimum": 0
    },
    "source_diversity": {
      "type": "integer",
      "minimum": 0
    },
    "last_validated_at": {
      "type": [
        "string",
        "null"
      ]
    }
  },
  "additionalProperties": false
}

proximens_geo_get_principle annotations

{
  "title": "Get GEO principle by ID",
  "readOnlyHint": true,
  "openWorldHint": false,
  "idempotentHint": true,
  "destructiveHint": false
}

proximens_geo_list_categories — List GEO principle categories

Advertised by the server during the last successful anonymous check.

Advertised read-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_list_categories input schema

{
  "type": "object",
  "properties": {},
  "description": "No input parameters",
  "additionalProperties": false
}

proximens_geo_list_categories output schema

{
  "type": "object",
  "required": [
    "categories",
    "total",
    "cached"
  ],
  "properties": {
    "total": {
      "type": "integer",
      "minimum": 0
    },
    "cached": {
      "type": "boolean"
    },
    "categories": {
      "type": "array",
      "items": {
        "type": "object",
        "required": [
          "category",
          "count"
        ],
        "properties": {
          "count": {
            "type": "integer",
            "minimum": 0
          },
          "category": {
            "type": "string"
          },
          "description": {
            "type": "string"
          }
        },
        "additionalProperties": false
      }
    }
  },
  "additionalProperties": false
}

proximens_geo_list_categories annotations

{
  "title": "List GEO principle categories",
  "readOnlyHint": true,
  "openWorldHint": false,
  "idempotentHint": true,
  "destructiveHint": false
}

proximens_geo_get_stats — Get GEO Engine statistics

Advertised by the server during the last successful anonymous check.

Advertised read-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_get_stats input schema

{
  "type": "object",
  "properties": {},
  "description": "No input parameters",
  "additionalProperties": false
}

proximens_geo_get_stats output schema

{
  "type": "object",
  "required": [
    "total_principles",
    "total_categories"
  ],
  "properties": {
    "tier_hint": {
      "type": "string"
    },
    "fetched_at": {
      "type": "string"
    },
    "total_evaluated": {
      "type": "integer",
      "minimum": 0
    },
    "total_categories": {
      "type": "integer",
      "minimum": 0
    },
    "total_principles": {
      "type": "integer",
      "minimum": 0
    },
    "last_validated_at": {
      "type": [
        "string",
        "null"
      ]
    },
    "last_distillation_at": {
      "type": [
        "string",
        "null"
      ]
    },
    "confidence_distribution": {
      "type": "object",
      "required": [
        ">=0.9",
        "0.8-0.9",
        "0.7-0.8",
        "<0.7"
      ],
      "properties": {
        "<0.7": {
          "type": "integer",
          "minimum": 0
        },
        ">=0.9": {
          "type": "integer",
          "minimum": 0
        },
        "0.7-0.8": {
          "type": "integer",
          "minimum": 0
        },
        "0.8-0.9": {
          "type": "integer",
          "minimum": 0
        }
      },
      "additionalProperties": false
    }
  },
  "additionalProperties": false
}

proximens_geo_get_stats annotations

{
  "title": "Get GEO Engine statistics",
  "readOnlyHint": true,
  "openWorldHint": false,
  "idempotentHint": true,
  "destructiveHint": false
}

proximens_geo_audit_url — Audit URL against Proximens GEO Engine

Advertised by the server during the last successful anonymous check.

Advertised read-onlyOpen-world

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_audit_url input schema

{
  "type": "object",
  "required": [
    "url"
  ],
  "properties": {
    "url": {
      "type": "string",
      "format": "uri",
      "description": "Target URL to audit"
    },
    "mode": {
      "enum": [
        "fast",
        "deep"
      ],
      "type": "string",
      "default": "fast",
      "description": "fast = quick signal checks (seconds); deep = full AI-synthesized consultancy report with sector benchmark (~30-50s)"
    },
    "max_issues": {
      "type": "integer",
      "default": 10,
      "maximum": 25,
      "minimum": 1,
      "description": "Maximum issues to return (default 10)"
    },
    "client_name": {
      "type": "string",
      "description": "Optional client identifier for the audit report header"
    },
    "branche_hint": {
      "type": "string",
      "description": "Branche hint in \"main:sub\" format, e.g. \"health_wellness:yoga_studio\". If omitted, principles are matched without branche filter."
    }
  },
  "additionalProperties": false
}

proximens_geo_audit_url output schema

{
  "type": "object",
  "required": [
    "audit_id",
    "url",
    "status"
  ],
  "properties": {
    "_wm": {
      "type": "string"
    },
    "url": {
      "type": "string"
    },
    "_meta": {
      "type": "object",
      "required": [
        "tier",
        "rate_limit_remaining",
        "processed_at"
      ],
      "properties": {
        "tier": {
          "enum": [
            "free",
            "pro",
            "enterprise"
          ],
          "type": "string"
        },
        "processed_at": {
          "type": "string"
        },
        "rate_limit_remaining": {
          "anyOf": [
            {
              "type": "number"
            },
            {
              "type": "string",
              "const": "unlimited"
            }
          ]
        }
      },
      "additionalProperties": false
    },
    "error": {
      "type": "string"
    },
    "score": {
      "type": "number",
      "maximum": 100,
      "minimum": 0
    },
    "sector": {
      "type": "object",
      "required": [
        "slug",
        "display_name_nl"
      ],
      "properties": {
        "slug": {
          "type": "string"
        },
        "display_name_nl": {
          "type": "string"
        }
      },
      "description": "Detected sector benchmark cohort (deep mode only)",
      "additionalProperties": false
    },
    "status": {
      "enum": [
        "complete",
        "failed"
      ],
      "type": "string"
    },
    "signals": {
      "type": "object",
      "required": [
        "structured_data_valid",
        "structured_data_invalid",
        "schema_types",
        "schema_flags",
        "h1_count",
        "images_total",
        "images_without_alt",
        "has_canonical",
        "hreflang_count",
        "has_viewport",
        "word_count",
        "render_source"
      ],
      "properties": {
        "h1_count": {
          "type": "integer",
          "minimum": 0
        },
        "word_count": {
          "type": "integer",
          "minimum": 0
        },
        "has_viewport": {
          "type": "boolean"
        },
        "images_total": {
          "type": "integer",
          "minimum": 0
        },
        "schema_flags": {
          "type": "object",
          "required": [
            "organization",
            "website",
            "faqPage",
            "product",
            "breadcrumbList",
            "localBusiness",
            "article"
          ],
          "properties": {
            "article": {
              "type": "boolean"
            },
            "faqPage": {
              "type": "boolean"
            },
            "product": {
              "type": "boolean"
            },
            "website": {
              "type": "boolean"
            },
            "organization": {
              "type": "boolean"
            },
            "localBusiness": {
              "type": "boolean"
            },
            "breadcrumbList": {
              "type": "boolean"
            }
          },
          "additionalProperties": false
        },
        "schema_types": {
          "type": "array",
          "items": {
            "type": "string"
          }
        },
        "has_canonical": {
          "type": "boolean"
        },
        "render_source": {
          "enum": [
            "firecrawl",
            "fetch-fallback"
          ],
          "type": "string"
        },
        "hreflang_count": {
          "type": "integer",
          "minimum": 0
        },
        "images_without_alt": {
          "type": "integer",
          "minimum": 0
        },
        "structured_data_valid": {
          "type": "integer",
          "minimum": 0
        },
        "structured_data_invalid": {
          "type": "integer",
          "minimum": 0
        }
      },
      "additionalProperties": false
    },
    "audit_id": {
      "type": "string",
      "format": "uuid"
    },
    "deep_mode": {
      "enum": [
        "ok",
        "timeout_fallback"
      ],
      "type": "string",
      "description": "Deep-mode outcome: ok = full synthesized report; timeout_fallback = synthesis exceeded budget, fast result returned"
    },
    "score_set": {
      "type": "object",
      "required": [
        "overallGEO",
        "aiCitability",
        "brandAuthority",
        "contentEEAT",
        "technicalGEO",
        "structuredData",
        "platformOptimization"
      ],
      "properties": {
        "overallGEO": {
          "type": [
            "number",
            "null"
          ]
        },
        "contentEEAT": {
          "type": [
            "number",
            "null"
          ]
        },
        "aiCitability": {
          "type": [
            "number",
            "null"
          ]
        },
        "technicalGEO": {
          "type": [
            "number",
            "null"
          ]
        },
        "brandAuthority": {
          "type": [
            "number",
            "null"
          ]
        },
        "structuredData": {
          "type": [
            "number",
            "null"
          ]
        },
        "platformOptimization": {
          "type": [
            "number",
            "null"
          ]
        }
      },
      "description": "7-dimension GEO scorecard (deep mode only)",
      "additionalProperties": false
    },
    "recommendations": {
      "type": "array",
      "items": {
        "type": "string"
      }
    },
    "report_markdown": {
      "type": "string"
    },
    "matched_principles": {
      "type": "array",
      "items": {
        "type": "object",
        "required": [
          "principle_id",
          "principle_title",
          "category",
          "severity",
          "finding",
          "suggestion",
          "confidence"
        ],
        "properties": {
          "excerpt": {
            "type": "string"
          },
          "finding": {
            "type": "string"
          },
          "category": {
            "type": "string"
          },
          "severity": {
            "enum": [
              "critical",
              "major",
              "minor"
            ],
            "type": "string"
          },
          "confidence": {
            "type": "number",
            "maximum": 1,
            "minimum": 0
          },
          "suggestion": {
            "type": "string"
          },
          "principle_id": {
            "type": "string",
            "format": "uuid"
          },
          "principle_title": {
            "type": "string"
          }
        },
        "additionalProperties": false
      }
    }
  },
  "additionalProperties": false
}

proximens_geo_audit_url annotations

{
  "title": "Audit URL against Proximens GEO Engine",
  "readOnlyHint": true,
  "openWorldHint": true,
  "idempotentHint": false,
  "destructiveHint": false
}

proximens_geo_compare_urls — Compare URLs against Proximens GEO Engine

Advertised by the server during the last successful anonymous check.

Advertised read-onlyOpen-world

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_compare_urls input schema

{
  "type": "object",
  "required": [
    "self_url",
    "competitor_url"
  ],
  "properties": {
    "self_url": {
      "type": "string",
      "format": "uri",
      "description": "Your URL to audit"
    },
    "competitor_url": {
      "type": "string",
      "format": "uri",
      "description": "Competitor URL to compare against"
    }
  },
  "additionalProperties": false
}

proximens_geo_compare_urls output schema

{
  "type": "object",
  "required": [
    "self_url",
    "competitor_url",
    "self_score",
    "competitor_score",
    "self_matched",
    "competitor_matched",
    "delta_principles",
    "insights"
  ],
  "properties": {
    "_meta": {
      "type": "object",
      "required": [
        "tier",
        "rate_limit_remaining",
        "processed_at"
      ],
      "properties": {
        "tier": {
          "enum": [
            "free",
            "pro",
            "enterprise"
          ],
          "type": "string"
        },
        "processed_at": {
          "type": "string"
        },
        "rate_limit_remaining": {
          "anyOf": [
            {
              "type": "number"
            },
            {
              "type": "string",
              "const": "unlimited"
            }
          ]
        }
      },
      "additionalProperties": false
    },
    "error": {
      "type": "string"
    },
    "insights": {
      "type": "array",
      "items": {
        "type": "string"
      }
    },
    "self_url": {
      "type": "string"
    },
    "self_score": {
      "type": "number",
      "maximum": 100,
      "minimum": 0
    },
    "self_matched": {
      "type": "array",
      "items": {
        "type": "object",
        "required": [
          "id",
          "title",
          "summary",
          "category",
          "confidence"
        ],
        "properties": {
          "id": {
            "type": "string",
            "format": "uuid"
          },
          "_wm": {
            "type": "string"
          },
          "title": {
            "type": "string"
          },
          "summary": {
            "type": "string"
          },
          "category": {
            "type": "string"
          },
          "full_text": {
            "type": "string"
          },
          "confidence": {
            "type": "number",
            "maximum": 1,
            "minimum": 0
          },
          "similarity": {
            "type": [
              "number",
              "null"
            ]
          },
          "source_url": {
            "anyOf": [
              {
                "type": "string",
                "format": "uri"
              },
              {
                "type": "null"
              }
            ]
          },
          "source_type": {
            "type": [
              "string",
              "null"
            ]
          },
          "upgrade_hint": {
            "type": "string"
          },
          "evidence_count": {
            "type": "integer",
            "minimum": 0
          }
        },
        "additionalProperties": false
      }
    },
    "competitor_url": {
      "type": "string"
    },
    "competitor_score": {
      "type": "number",
      "maximum": 100,
      "minimum": 0
    },
    "delta_principles": {
      "type": "object",
      "required": [
        "missing_on_self",
        "missing_on_competitor"
      ],
      "properties": {
        "missing_on_self": {
          "type": "array",
          "items": {
            "$ref": "#/properties/self_matched/items"
          }
        },
        "missing_on_competitor": {
          "type": "array",
          "items": {
            "$ref": "#/properties/self_matched/items"
          }
        }
      },
      "additionalProperties": false
    },
    "competitor_matched": {
      "type": "array",
      "items": {
        "$ref": "#/properties/self_matched/items"
      }
    }
  },
  "additionalProperties": false
}

proximens_geo_compare_urls annotations

{
  "title": "Compare URLs against Proximens GEO Engine",
  "readOnlyHint": true,
  "openWorldHint": true,
  "idempotentHint": false,
  "destructiveHint": false
}

proximens_geo_synthesize_brief — Synthesize Content Brief from Proximens GEO Engine

Advertised by the server during the last successful anonymous check.

Advertised read-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.

proximens_geo_synthesize_brief input schema

{
  "type": "object",
  "required": [
    "topic"
  ],
  "properties": {
    "topic": {
      "type": "string",
      "maxLength": 200,
      "minLength": 3
    },
    "target_branche": {
      "enum": [
        "local_services",
        "digital_services",
        "product_commerce",
        "creative_professional",
        "health_wellness",
        "b2b_saas",
        "universal"
      ],
      "type": "string"
    },
    "competitor_urls": {
      "type": "array",
      "items": {
        "type": "string",
        "format": "uri"
      },
      "maxItems": 3
    },
    "word_count_target": {
      "type": "number",
      "default": 1500,
      "maximum": 5000,
      "minimum": 300
    }
  },
  "additionalProperties": false
}

proximens_geo_synthesize_brief output schema

{
  "type": "object",
  "required": [
    "brief_id",
    "topic",
    "suggested_structure",
    "principles_to_address",
    "estimated_word_count"
  ],
  "properties": {
    "_meta": {
      "type": "object",
      "required": [
        "tier",
        "rate_limit_remaining",
        "processed_at"
      ],
      "properties": {
        "tier": {
          "enum": [
            "free",
            "pro",
            "enterprise"
          ],
          "type": "string"
        },
        "processed_at": {
          "type": "string"
        },
        "rate_limit_remaining": {
          "anyOf": [
            {
              "type": "number"
            },
            {
              "type": "string",
              "const": "unlimited"
            }
          ]
        }
      },
      "additionalProperties": false
    },
    "topic": {
      "type": "string"
    },
    "brief_id": {
      "type": "string",
      "format": "uuid"
    },
    "schema_markup": {
      "type": "array",
      "items": {
        "type": "object",
        "required": [
          "type",
          "rationale"
        ],
        "properties": {
          "type": {
            "type": "string"
          },
          "rationale": {
            "type": "string"
          }
        },
        "additionalProperties": false
      }
    },
    "faq_suggestions": {
      "type": "array",
      "items": {
        "type": "object",
        "required": [
          "q",
          "a_hint"
        ],
        "properties": {
          "q": {
            "type": "string"
          },
          "a_hint": {
            "type": "string"
          }
        },
        "additionalProperties": false
      }
    },
    "suggested_structure": {
      "type": "object",
      "required": [
        "h1",
        "sections"
      ],
      "properties": {
        "h1": {
          "type": "string"
        },
        "sections": {
          "type": "array",
          "items": {
            "type": "object",
            "required": [
              "h2",
              "key_points"
            ],
            "properties": {
              "h2": {
                "type": "string"
              },
              "key_points": {
                "type": "array",
                "items": {
                  "type": "string"
                }
              }
            },
            "additionalProperties": false
          }
        }
      },
      "additionalProperties": false
    },
    "estimated_word_count": {
      "type": "number"
    },
    "principles_to_address": {
      "type": "array",
      "items": {
        "type": "object",
        "required": [
          "id",
          "title",
          "summary",
          "category",
          "confidence"
        ],
        "properties": {
          "id": {
            "type": "string",
            "format": "uuid"
          },
          "_wm": {
            "type": "string"
          },
          "title": {
            "type": "string"
          },
          "summary": {
            "type": "string"
          },
          "category": {
            "type": "string"
          },
          "full_text": {
            "type": "string"
          },
          "confidence": {
            "type": "number",
            "maximum": 1,
            "minimum": 0
          },
          "similarity": {
            "type": [
              "number",
              "null"
            ]
          },
          "source_url": {
            "anyOf": [
              {
                "type": "string",
                "format": "uri"
              },
              {
                "type": "null"
              }
            ]
          },
          "source_type": {
            "type": [
              "string",
              "null"
            ]
          },
          "upgrade_hint": {
            "type": "string"
          },
          "evidence_count": {
            "type": "integer",
            "minimum": 0
          }
        },
        "additionalProperties": false
      }
    }
  },
  "additionalProperties": false
}

proximens_geo_synthesize_brief annotations

{
  "title": "Synthesize Content Brief from Proximens GEO Engine",
  "readOnlyHint": true,
  "openWorldHint": false,
  "idempotentHint": false,
  "destructiveHint": false
}

proximens_geo_bulk_search — Bulk Search Proximens GEO Engine

Advertised by the server during the last successful anonymous check.

Advertised read-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_bulk_search input schema

{
  "type": "object",
  "required": [
    "queries"
  ],
  "properties": {
    "queries": {
      "type": "array",
      "items": {
        "type": "string",
        "maxLength": 500,
        "minLength": 3
      },
      "maxItems": 100,
      "minItems": 2
    },
    "category": {
      "enum": [
        "technical",
        "structured-data",
        "content",
        "ai-search",
        "freshness",
        "multimodal",
        "user-signals",
        "e-e-a-t",
        "mobile",
        "performance",
        "query-intent",
        "internal-linking",
        "other"
      ],
      "type": "string"
    },
    "top_k_per_query": {
      "type": "number",
      "default": 5,
      "maximum": 10,
      "minimum": 1
    }
  },
  "additionalProperties": false
}

proximens_geo_bulk_search output schema

{
  "type": "object",
  "required": [
    "results",
    "total_queries",
    "total_matches"
  ],
  "properties": {
    "_meta": {
      "type": "object",
      "required": [
        "tier",
        "rate_limit_remaining",
        "processing_time_ms",
        "processed_at"
      ],
      "properties": {
        "tier": {
          "enum": [
            "free",
            "pro",
            "enterprise"
          ],
          "type": "string"
        },
        "processed_at": {
          "type": "string"
        },
        "processing_time_ms": {
          "type": "number"
        },
        "rate_limit_remaining": {
          "anyOf": [
            {
              "type": "number"
            },
            {
              "type": "string",
              "const": "unlimited"
            }
          ]
        }
      },
      "additionalProperties": false
    },
    "results": {
      "type": "array",
      "items": {
        "type": "object",
        "required": [
          "query",
          "matches",
          "count"
        ],
        "properties": {
          "count": {
            "type": "number"
          },
          "query": {
            "type": "string"
          },
          "matches": {
            "type": "array",
            "items": {
              "type": "object",
              "required": [
                "id",
                "title",
                "summary",
                "category",
                "confidence"
              ],
              "properties": {
                "id": {
                  "type": "string",
                  "format": "uuid"
                },
                "_wm": {
                  "type": "string"
                },
                "title": {
                  "type": "string"
                },
                "summary": {
                  "type": "string"
                },
                "category": {
                  "type": "string"
                },
                "full_text": {
                  "type": "string"
                },
                "confidence": {
                  "type": "number",
                  "maximum": 1,
                  "minimum": 0
                },
                "similarity": {
                  "type": [
                    "number",
                    "null"
                  ]
                },
                "source_url": {
                  "anyOf": [
                    {
                      "type": "string",
                      "format": "uri"
                    },
                    {
                      "type": "null"
                    }
                  ]
                },
                "source_type": {
                  "type": [
                    "string",
                    "null"
                  ]
                },
                "upgrade_hint": {
                  "type": "string"
                },
                "evidence_count": {
                  "type": "integer",
                  "minimum": 0
                }
              },
              "additionalProperties": false
            }
          }
        },
        "additionalProperties": false
      }
    },
    "total_matches": {
      "type": "number"
    },
    "total_queries": {
      "type": "number"
    }
  },
  "additionalProperties": false
}

proximens_geo_bulk_search annotations

{
  "title": "Bulk Search Proximens GEO Engine",
  "readOnlyHint": true,
  "openWorldHint": false,
  "idempotentHint": true,
  "destructiveHint": false
}

Prompts

Not advertised

No prompt definitions available.

Resources

Not advertised

No resource definitions available.

90-day uptime

A lightweight connection check about every six hours, sampled on hosts with many listings. It shows the server answered, not that its tools work.

Too few checks for a percentage yet (2 of 2 answered).

2026-11-06: 1 of 1 checks answered
2026-11-07: 1 of 1 checks answered

30-day availability

Aggregated from read-only remote checks; this is not a tool-execution or security guarantee.

Successful checks: 1 of 1 (100%)
Average latency: 663 ms
95th percentile latency: 663 ms

Maintenance history

Public check and source-refresh events. Editorial and ownership records remain private.

Nov 6, 2026, 3:46 PM UTC · probe · passed · 663 ms · metadata changed · 8 tool(s)

Connect from your client

Each snippet registers the same endpoint; pick the client you use.

This server is operated by the named third party. Listing and endpoint checks are not an endorsement or a security audit. Review the operator's permissions, terms, and data handling before connecting. How listings are checked and corrected.

Claude Code

Run this once in a terminal. It registers the remote server. Use --scope project to write .mcp.json for the repo.

Claude Code configuration

claude mcp add --transport http proximens-geo-engine-mcp https://www.proximens.nl/mcp

Codex

Run this once. Codex stores MCP servers in ~/.codex/config.toml (or .codex/config.toml in a trusted project).

Codex configuration

codex mcp add proximens-geo-engine-mcp --url https://www.proximens.nl/mcp

Cursor

Merge this server into .cursor/mcp.json in your project, then enable proximens-geo-engine-mcp in your MCP settings.

Cursor configuration

{
  "mcpServers": {
    "proximens-geo-engine-mcp": {
      "url": "https://www.proximens.nl/mcp"
    }
  }
}

Cline

Merge this into cline_mcp_settings.json (Cline → MCP Servers → Configure).

Cline configuration

{
  "mcpServers": {
    "proximens-geo-engine-mcp": {
      "type": "streamableHttp",
      "url": "https://www.proximens.nl/mcp",
      "disabled": false
    }
  }
}

VS Code

Merge this server into .vscode/mcp.json. Use MCP: List Servers to start proximens-geo-engine-mcp and inspect its tools.

VS Code configuration

{
  "servers": {
    "proximens-geo-engine-mcp": {
      "type": "http",
      "url": "https://www.proximens.nl/mcp"
    }
  }
}

Gemini CLI

Run this once. It writes .gemini/settings.json in the current project; pass --scope user for ~/.gemini/settings.json.

Gemini CLI configuration

gemini mcp add --transport http proximens-geo-engine-mcp https://www.proximens.nl/mcp

Claude Desktop

Open Claude Settings > Connectors > Add custom connector, enter this server URL and enable it for the conversation. This is a manual remote-connector handoff, not a desktop JSON configuration.

Claude Desktop configuration

https://www.proximens.nl/mcp

Windsurf

Merge this into ~/.codeium/windsurf/mcp_config.json, then refresh MCP in Cascade. Windsurf remote servers use serverUrl, not url.

Windsurf configuration

{
  "mcpServers": {
    "proximens-geo-engine-mcp": {
      "serverUrl": "https://www.proximens.nl/mcp"
    }
  }
}

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Proximens GEO Engine MCP

Endpoint and access

What its tools do

Read-only (8)

Checks and signals

What you can do with it

Source and maintenance

Protocol and capabilities

Tools

Prompts

Resources

90-day uptime

30-day availability

Maintenance history

Connect from your client

Claude Code

Codex

Cursor

Cline

VS Code

Gemini CLI

Claude Desktop

Windsurf

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