Ninar AI
Audit your brand's visibility across ChatGPT, Gemini, Claude, Perplexity + 6 more engines.
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Calidad y seguridad
Basado en el análisis automatizado de las definiciones de herramientas y el cumplimiento del protocolo.
Costo de contexto
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-httpQué puede hacer
Inventario de herramientas
Herramientas (5)
🟢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
get_latest_scoreget_latest_scorelist_content_gapslist_content_gapslist_content_gapsget_latest_scoreComunidad
Evidencia