Ninar AI

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Audit your brand's visibility across ChatGPT, Gemini, Claude, Perplexity + 6 more engines.

Marketing & SEO

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Tool list from our last check. Connect live to refresh it.

audit_brand_visibility Read-only

Check whether a brand or entity surfaced by an AI engine is a genuine competitor in your category (e.g. is 'Banner Life' actually a mortgage insurance competitor to Enact?). Uses dual-model verification with automatic escalation on disagreement. Returns a confirmed/rejected decision, confidence score, reasoning, and audit trail. Pro plan or higher required.

entitystring, required

Entity name to adjudicate, e.g. 'Banner Life', 'Enact Solar'.

raw_evidenceobject, required

Source text the entity appeared in. Should contain 'raw_answer_excerpt' and optionally 'entity_sentence' and 'source_probe_id'.

taxonomy_idstring

Taxonomy registry to validate against. Default: pmi.v1

Tools (5)

audit_brand_visibility

read-only

Argument	Type	Description
entity*	string	Entity name to adjudicate, e.g. 'Banner Life', 'Enact Solar'.
taxonomy_id	string	Taxonomy registry to validate against. Default: pmi.v1
raw_evidence*	object	Source text the entity appeared in. Should contain 'raw_answer_excerpt' and optionally 'entity_sentence' and 'source_probe_id'.

Input schema (JSON)

{
  "type": "object",
  "required": [
    "entity",
    "raw_evidence"
  ],
  "properties": {
    "entity": {
      "type": "string",
      "description": "Entity name to adjudicate, e.g. 'Banner Life', 'Enact Solar'."
    },
    "taxonomy_id": {
      "type": "string",
      "description": "Taxonomy registry to validate against. Default: pmi.v1"
    },
    "raw_evidence": {
      "type": "object",
      "required": [
        "raw_answer_excerpt"
      ],
      "properties": {
        "entity_sentence": {
          "type": "string"
        },
        "source_probe_id": {
          "type": "string"
        },
        "raw_answer_excerpt": {
          "type": "string"
        }
      },
      "description": "Source text the entity appeared in. Should contain 'raw_answer_excerpt' and optionally 'entity_sentence' and 'source_probe_id'."
    }
  }
}

generate_content

Generate AI-optimized content (FAQ, about copy, use cases, differentiators) for the gaps in your latest scan. Returns full content text inline — no need to visit the dashboard. Pro plan or higher required. Pass gap_type='all' to get every block in one call.

Argument	Type	Description
gap_type*	string	Which content block to generate. Use 'all' for everything in one call.

Input schema (JSON)

{
  "type": "object",
  "required": [
    "gap_type"
  ],
  "properties": {
    "gap_type": {
      "enum": [
        "faq",
        "about",
        "use_cases",
        "differentiators",
        "all"
      ],
      "type": "string",
      "description": "Which content block to generate. Use 'all' for everything in one call."
    }
  }
}

get_latest_score

Get the AI Visibility Index (0-100) for the signed-in user's most recently scanned brand, broken down by engine. Requires a free Ninar account (no credit card).

read-only

No arguments.

Input schema (JSON)

{
  "type": "object",
  "properties": {}
}

list_content_gaps

List AI-generated content suggestions (FAQs, differentiators, use cases, about copy) the signed-in user can publish to close visibility gaps found in their latest scan.

read-only

No arguments.

Input schema (JSON)

{
  "type": "object",
  "properties": {}
}

scan_visibility

Run an AI visibility scan for a brand. Pass `city` for a local-business check (ChatGPT + Gemini, city-scoped). Omit `city` for a multi-engine GEO scan across ChatGPT, Gemini, Perplexity, Claude, AI Overviews — engine count scales with the user's Ninar plan (free = 2).

Argument	Type	Description
city	string	City for a local-business check. Omit for multi-engine GEO scan.
country	string	Optional ISO country: us, gb, in, eu.
website	string	Optional brand URL for GEO citation matching.
category*	string	Category, e.g. 'AI visibility platform', 'pizza restaurant'.
use_case	string	Optional GEO use case, e.g. 'for sales teams'.
brand_name*	string	Brand to scan, e.g. 'Ninar', 'Joe's Pizza'.

Input schema (JSON)

{
  "type": "object",
  "required": [
    "brand_name",
    "category"
  ],
  "properties": {
    "city": {
      "type": "string",
      "description": "City for a local-business check. Omit for multi-engine GEO scan."
    },
    "country": {
      "type": "string",
      "description": "Optional ISO country: us, gb, in, eu."
    },
    "website": {
      "type": "string",
      "description": "Optional brand URL for GEO citation matching."
    },
    "category": {
      "type": "string",
      "description": "Category, e.g. 'AI visibility platform', 'pizza restaurant'."
    },
    "use_case": {
      "type": "string",
      "description": "Optional GEO use case, e.g. 'for sales teams'."
    },
    "brand_name": {
      "type": "string",
      "description": "Brand to scan, e.g. 'Ninar', 'Joe's Pizza'."
    }
  }
}