AIReady

Scan and fix your site's AI discoverability: crawler access, llms.txt, JSON-LD. Free.

Sollte ich dies verwenden

Qualität und Sicherheit

A
Qualität der Beschreibung
96%
Vollständigkeit des Schemas
74%
Qualität der Benennung
84%
Risiko der Vergiftung
100%
Übereinstimmung der Berechtigungen
100%
Einhaltung des Protokolls
100%

Basierend auf einer automatisierten Analyse der Tool-Definitionen und der Einhaltung des Protokolls.

Kontextkosten

~691Tokens (Tool-Definitionen)
~730 BTypische Antwortgröße
Mittlere Auswirkung auf die Aufmerksamkeit (0.54% von 128k Kontext)

Dies ist die ungefähre Anzahl der Tokens, die jedes Mal verbraucht werden, wenn die Tools des Servers in den Kontext eines Modells geladen werden. Höhere Werte verringern die Aufmerksamkeit, die für andere Aufgaben verfügbar ist.

Installieren

Installation mit einem Klick

Fügen Sie dies Ihrer Datei `claude_desktop_config.json` hinzu:

{
  "mcpServers": {
    "ai-ready": {
      "url": "https://ai-ready.magicteams.ai/mcp"
    }
  }
}

Remote-Endpunkte

https://ai-ready.magicteams.ai/mcpstreamable-http

Was es kann

Tool-Inventar

Tools (5)

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🟢check_ai_readiness(domain)

Scan a domain for AI discoverability: which AI crawlers robots.txt blocks or allows (GPTBot, OAI-SearchBot, ClaudeBot, PerplexityBot...), llms.txt presence, sitemap, schema.org data, meta and Content Signals. Fetches only /robots.txt, /llms.txt, /sitemap.xml and the homepage over HTTPS.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "domain": {
      "type": "string",
      "description": "Domain or URL, e.g. example.com"
    }
  },
  "required": [
    "domain"
  ]
}
🟢crawler_policy_guide

Reference table of AI crawlers (owner, purpose, whether they drive AI visibility or training) with rules of thumb for allowing or blocking each.

Eingabe-Schema

{
  "type": "object",
  "properties": {},
  "required": []
}
🟢robots_txt_for_ai(policy, sitemap_url, content_signals)

Generate robots.txt rules for a chosen AI policy (max visibility, search-only, block training, block all AI), optionally with Content-Signal lines and a sitemap reference.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "policy": {
      "type": "string",
      "enum": [
        "max_visibility",
        "search_only",
        "block_training",
        "block_all_ai"
      ]
    },
    "sitemap_url": {
      "type": "string"
    },
    "content_signals": {
      "type": "boolean"
    }
  },
  "required": [
    "policy"
  ]
}
🟢llms_txt_draft(business_name, description, key_pages, contact_email)

Draft a starter llms.txt from your business name, one-line description, key pages and contact so AI agents get a curated summary of your site.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "business_name": {
      "type": "string"
    },
    "description": {
      "type": "string"
    },
    "key_pages": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "title": {
            "type": "string"
          },
          "url": {
            "type": "string"
          },
          "note": {
            "type": "string"
          }
        },
        "required": [
          "title",
          "url"
        ]
      }
    },
    "contact_email": {
      "type": "string"
    }
  },
  "required": [
    "business_name",
    "description"
  ]
}
🟢schema_jsonld_sample(type, name, url, description, telephone, ...)

Generate a schema.org JSON-LD snippet (Organization, LocalBusiness, Product or FAQ) to paste into your page head for AI identification.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "type": {
      "type": "string",
      "enum": [
        "organization",
        "local_business",
        "product",
        "faq"
      ]
    },
    "name": {
      "type": "string"
    },
    "url": {
      "type": "string"
    },
    "description": {
      "type": "string"
    },
    "telephone": {
      "type": "string"
    },
    "address": {
      "type": "string"
    },
    "price": {
      "type": "string"
    },
    "questions": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "question": {
            "type": "string"
          },
          "answer": {
            "type": "string"
          }
        },
        "required": [
          "question",
          "answer"
        ]
      }
    }
  },
  "required": [
    "type",
    "name",
    "url"
  ]
}

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Aktuelle Beobachtungen

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