Ninar AI

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

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Calidad y seguridad

A
Calidad de la descripción
100%
Integridad del esquema
72%
Calidad de los nombres
96%
Riesgo de envenenamiento
100%
Coincidencia de permisos
100%
Cumplimiento del protocolo
100%

Basado en el análisis automatizado de las definiciones de herramientas y el cumplimiento del protocolo.

Costo de contexto

~892Tokens (definiciones de herramientas)
~928 BTamaño de respuesta típico
Impacto moderado en la atención (0.70% del contexto de 128k)

Este es el número aproximado de tokens que se consumen cada vez que las herramientas del servidor se cargan en el contexto de un modelo. Los recuentos más altos reducen la atención disponible para otras tareas.

Instalar

Instalación con un clic

Agrega esto a tu archivo `claude_desktop_config.json`:

{
  "mcpServers": {
    "ninar": {
      "url": "https://ninar.ai/mcp"
    }
  }
}

Puntos de conexión remotos

https://ninar.ai/mcpstreamable-http

Qué puede hacer

Inventario de herramientas

Herramientas (5)

🟢 Solo lectura🟡 Escritura🔴 Eliminación⚪ Desconocido
🟢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).

Esquema de entrada

{
  "type": "object",
  "properties": {}
}
🟢scan_visibility(brand_name, category, city, country, use_case, ...)

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).

Esquema de entrada

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

Esquema de entrada

{
  "type": "object",
  "properties": {}
}
🟢generate_content(gap_type)

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.

Esquema de entrada

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

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.

Esquema de entrada

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

Prompts recomendados

retrieve_data
Get details about [item] from Ninar AI
Herramientas esperadas: get_latest_score
fetch_info
Fetch [information type] using Ninar AI
Herramientas esperadas: get_latest_score
list_items
List all [items] available in Ninar AI
Herramientas esperadas: list_content_gaps
browse_collection
Show me the [collection] from Ninar AI
Herramientas esperadas: list_content_gaps
explore_workflow
List available [items], then get details for each one using Ninar AI
Herramientas esperadas: list_content_gapsget_latest_score

Comunidad

Califica este servidor

Evidencia

Observaciones recientes

verificadoversión no registrada5 herramientas
verificadoversión no registrada5 herramientas