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Ai Visibility MCP Server

@krissanders

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その他

トランスポート

stdio

作者

krissanders

投稿者

krissanders

Ai Visibility MCP Server について

MCP server that audits AI-bot visibility. Reports per-bot robots.txt verdicts for 22 AI user-agents (GPTBot, ClaudeBot, PerplexityBot, Google-Extended, etc.), Cloudflare AI-default flags, on-page schema, sitemap, llms.txt, SPA-shell detection, and cross-model brand mentions via P

#seo#marketing#ai-visibility#llm-citations#robots-txt#schema-org#cloudflare#gptbot#claudebot#perplexity#brand-monitoring#audit

Ai Visibility MCP Server の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "ai-visibility": {
      "command": "uv",
      "args": [
        "--directory",
        "/abs/path/to/ai-visibility-mcp",
        "run",
        "ai-visibility-mcp"
      ],
      "env": {
        "PERPLEXITY_API_KEY": "<your-key>",
        "OPENROUTER_API_KEY": "<your-key>"
      }
    }
  }
}

Ai Visibility MCP Server のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is Ai Visibility Mcp?

Ai Visibility Mcp is an MCP server that audits how AI sees a website—checking robots.txt, structured data, LLM brand mentions, and Cloudflare AI defaults in a single tool call. It is built for website owners and marketing teams who need to understand and improve their site's visibility to AI search engines and chatbots.

How to use Ai Visibility Mcp?

Requires Python 3.10+ and uv. Clone the repository, run uv sync, copy .env.example to .env and fill in PERPLEXITY_API_KEY and OPENROUTER_API_KEY. Run with uv run ai-visibility-mcp for stdio transport (Claude Desktop/Code) or uv run ai-visibility-mcp --http --port 8000 for HTTP transport. Configure as an MCP server in Claude Desktop config or .claude.json.

Key features of Ai Visibility Mcp

  • check_ai_bot_access(domain)—per-bot robots.txt analysis for 22 AI user-agents
  • audit_ai_visibility(domain)—0–100 composite score with explainable deductions
  • check_llm_mention(brand, query, aliases?, models?)—cross-model brand surfacing
  • compare_competitors(your_domain, competitor_domains[])—parallel ranked audit, max 10 in flight
  • SSRF guard, daily spend cap, and per-call cost ceiling

Use cases of Ai Visibility Mcp

  • Determine whether AI bots (GPTBot, ClaudeBot, PerplexityBot) are blocked from your site
  • Get an overall AI visibility score with line-item deductions for missing structure data or sitemaps
  • Measure your brand's share of voice in LLM-generated answers across multiple models
  • Benchmark your site's AI accessibility against up to 10 competitors simultaneously

よくある質問

1

What dependencies and runtime requirements does Ai Visibility Mcp have?

Python 3.10+ is required, along with the `uv` package manager. For LLM brand-mention checks, `PERPLEXITY_API_KEY` and `OPENROUTER_API_KEY` must be set in the environment.

2

What data does Ai Visibility Mcp persist?

No user content is logged to disk. The only persistence is a daily spend ledger (default `~/.cache/ai-visibility-mcp/spend.json`) used to enforce the `MAX_DAILY_USD` cap.

3

What transport and authentication options are available?

Ai Visibility Mcp supports stdio transport (for Claude Desktop/Code) and HTTP transport (for remote agents). No built-in authentication on the HTTP transport is mentioned; security relies on the SSRF guard and spend caps.

4

What are the known limits of Ai Visibility Mcp?

The `compare_competitors` tool supports a maximum of 10 domains in flight. LLM calls are bounded by a per-call cost ceiling (`MAX_COST_PER_CALL`, default $0.10) and a daily spend cap (`MAX_DAILY_USD`, default $5.00). Output tokens are capped at 1024 per call. Persistent diff tracking is deferred to a future release.

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