Ninar AI

ninar-ctrl/ninar.ai

If you're tracking how ChatGPT, Gemini, Claude, and other AI engines mention your brand in their responses, this server connects you to Ninar's visibility scanning platform. It exposes operations to run brand audits across nine AI engines, pull visibility scores, identify content gaps, and check which queries return your brand versus competitors. You get location-specific scans, before and after tracking, and competitive benchmarking data. Useful when you need programmatic access to AI brand presence metrics without leaving your editor or workflow, especially if you're optimizing content for generative engine recommendations or building visibility dashboards for clients.

tools: 5
transport: HTTP
last updated: May 21, 2026

View on GitHub

Install

From registry metadata

$ npx add-mcp https://ninar.ai/mcp --name ninar

Run in your terminal. add-mcp asks which agents to add it to (Claude Code, Codex, Cursor and more). Add -g to install it for every project.

Review the command, arguments and environment values before installing. MCP servers run with your local permissions.

Other ways

Claude Code

$ claude mcp add --transport http ninar https://ninar.ai/mcp

Run in your terminal. Add --scope user to make it available in every project.

Tools

Verified live · 5 tools

Verified live against the running server on Nov 6, 2026.

get_latest_scoreGet 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).

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).

No parameters. Call it with no arguments.

scan_visibilityRun 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).6 params

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).

Parameters* required

brand_name*string

Brand to scan, e.g. 'Ninar', 'Joe's Pizza'.

category*string

Category, e.g. 'AI visibility platform', 'pizza restaurant'.

citystring

City for a local-business check. Omit for multi-engine GEO scan.

countrystring

Optional ISO country: us, gb, in, eu.

use_casestring

Optional GEO use case, e.g. 'for sales teams'.

websitestring

Optional brand URL for GEO citation matching.

list_content_gapsList 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.

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.

No parameters. Call it with no arguments.

generate_contentGenerate 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.1 params

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.

Parameters* required

gap_type*string

Which content block to generate. Use 'all' for everything in one call.one of faq · about · use_cases · differentiators · all

audit_brand_visibilityCheck 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 de...3 params

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 de...

Parameters* required

entity*string

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

raw_evidence*object

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

Readme

Details

Repository: github.com/ninar-ctrl/ninar.ai
Website: ninar.ai
Category: AI & LLM Tools
Transport: HTTP
Registry: MCP registry, active
Tools verified: Nov 6, 2026

Related AI & LLM Tools MCP servers

View all

Scout by Optimlyai.optimly/scoutQuery the AI Brand Directory. Audit brand visibility in ChatGPT, Claude, and Gemini.0stars

OrgGen AIorggen-ai/orggen-mcpHuman-agent interface for projects: you prioritize and decide, your AI agents execute. Over MCP.0stars

Mcpsitepulsar/mcp-serverSitePulsar AEO audits: fetch FIND/READ/USE agent-readiness scores for any website.0stars

Stompy – AI Memory for Claude & MCP Agentsbanton/stompy-mcp-serverPersistent AI memory with semantic search, conflict detection, and ticketing.0stars

Canonical Company Searchai.trycanonical/company-searchVerified, long-tail company search: describe what you want, get an LLM-verified company shortlist.0stars

Docktry-dock-ai/mcpAI workspace for you, your team, and every agent. Tables, docs (images, 4K video), formulas.0stars