N Gram Frequency EngineをChatGPTとClaudeに接続

• 01 / 02感情トレンドを分析する方法
• 02 / 02キーワードパターンを分析する

最速日

679ms

最遅日

937ms

14日間の傾向

遅延傾向+15%

natural Connector

準備完了です。MCPクライアントを選択し、セットアップ手順に従ってください。

コネクタリンクhttps://edge.vinkius.com/vk_preview_9T1etKMahiW8NnGArHZFRlQgidDXjNxOPOUMepVx/mcpコピー

Claude Desktop

以下の手順で数秒で接続できます。

1. 1In Claude Desktop, open Settings → Connectors.
2. 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
3. 3Click Add and start a new chat — natural capabilities are ready to use.

設定 · claude_desktop_config.jsonコピー

{
  "mcpServers": {
    "n-gram-frequency-engine-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_9T1etKMahiW8NnGArHZFRlQgidDXjNxOPOUMepVx/mcp"
    }
  }
}

• Claude
• ChatGPT
• Cursor
• VS Code
• Windsurf
• Claude Code
• JetBrains
• Cline

各クライアントの手順ガイドはこちらです。 接続方法

Claude向けのガイド付きセットアップ？ naturalをClaudeや他のAIに設定する

このConnectorが対応するすべてのAIクライアントを見る ↑

• 01

  SEOスペシャリスト

  競合サイトのコンテンツから、頻出するキーワードフレーズを正確に特定し、戦略に活用します。

• 02

  データサイエンティスト

  自然言語処理（NLP）において、LLMの近似値に頼らない、数学的に正確な統計データが必要な場面で使用します。

• 03

  コンテンツアナリスト

  膨大な文書やレビュー群から、特定のフレーズの出現傾向を定量的に分析します。

• 01

  Why not just ask the LLM to count the words?

  LLMs are probabilistic and struggle with precise counting, especially in long texts. This MCP uses JavaScript to provide mathematically certain results that an LLM cannot guarantee.

• 02

  Can I use this for 4-word phrases?

  Yes. The capability supports custom N-Gram lengths, meaning you can request bigrams, trigrams, 4-grams, or any other length.

• 03

  Does this work with long PDFs?

  Yes. Because the processing happens via the MCP rather than inside the LLM's context window, it can handle much larger amounts of text without hitting token limits.

• 04

  Which AI clients can use this MCP?

  Any MCP-compatible client, including Claude, Cursor, Windsurf, and VS Code, can use this capability once connected through Vinkius.

• 05

  Is the counting accurate?

  The counting is deterministic. It uses native JavaScript execution to ensure the results are mathematically perfect every time.

• 06

  What are Bigrams and Trigrams?

  A bigram is a sequence of two adjacent words (e.g., 'machine learning'). A trigram is three (e.g., 'natural language processing').

• 07

  Does it lowercase the text automatically?

  Yes, all text is automatically lowercased and tokenized natively to ensure accurate aggregation of phrases.

• 08

  Is this faster than asking Claude?

  Significantly faster and 100% accurate. LLMs cannot count occurrences across thousands of tokens reliably.

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  Natural Tokenizer Engine AIコネクタ

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