AI Visibility Index
AI visibility rankings for 104 Japanese EC companies across ChatGPT, Claude, Gemini, Perplexity.
Should I use this
Quality & Safety
Based on automated analysis of tool definitions and protocol compliance.
Context Cost
This is the approximate number of tokens consumed each time the server's tools are loaded into a model's context. Higher counts reduce the attention available for other tasks.
Install
One-Click Install
Add this to your `claude_desktop_config.json` file:
{
"mcpServers": {
"mcp-ai-visibility-index": {
"url": "https://ai-visibility-index.dev/mcp"
}
}
}Remote endpoints
https://ai-visibility-index.dev/mcpstreamable-httpWhat it can do
Tool inventory
Tools (3)
🟢check_ai_visibility(domain)
Check the AI visibility (LLMO/GEO) score for a specific domain. Returns the overall score (0-100), scores from 4 AI engines (ChatGPT, Claude, Gemini, Perplexity), citation rate, and industry ranking. Data is based on the AI Visibility Index monthly scan of 104 Japanese EC companies. Useful for LLMO (Large Language Model Optimization) and GEO (Generative Engine Optimization) analysis. | 日本EC企業104社のAI検索可視性スコアをドメイン指定で照会。
Input Schema
{
"type": "object",
"properties": {
"domain": {
"type": "string",
"description": "Domain to check, e.g. \"amazon.co.jp\", \"zozo.jp\", \"uniqlo.com/jp\". Partial matches are supported."
}
},
"required": [
"domain"
]
}🟢list_ai_visibility_industries
List all industries covered by the AI Visibility Index with their average LLMO/GEO scores, company counts, and score ranges. Currently covers 9 Japanese EC industries with 104 companies total. | 9業界のAI可視性スコア平均・企業数・スコア範囲を一覧表示。
Input Schema
{
"type": "object",
"properties": {}
}🟢get_ai_visibility_methodology
Get the AI Visibility Index scoring methodology: how LLMO/GEO scores are calculated, which AI engines are tested (ChatGPT, Claude, Gemini, Perplexity), query types, scoring formula, and data freshness. | スコアリング方法論（計算式・対象エンジン・クエリ種別・データ更新頻度）。
Input Schema
{
"type": "object",
"properties": {}
}Community
Evidence