Claude Verbosity OptimizerをAIに接続

最速日

657ms

最遅日

1138ms

14日間の傾向

安定-4%

Claude Verbosity Optimizer 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_o44ZVazVB52xpsAJcQG0LRASjEKYUJlpy6vxfAUE/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 — Claude Verbosity Optimizer capabilities are ready to use.

設定 · claude_desktop_config.jsonコピー

{
  "mcpServers": {
    "claude-verbosity-optimizer-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_o44ZVazVB52xpsAJcQG0LRASjEKYUJlpy6vxfAUE/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？ Claude Verbosity Optimizer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

  Software Engineers

  They hand off large codebases and file lists to agents in Cursor or Windsurf.

• 02

  AI Prompt Engineers

  They need to keep context windows clean to maintain model performance.

• 03

  Data Analysts

  They use it to manage large text outputs when working with heavy datasets.

• 01

  How is this different from asking the AI to summarize?

  Summarization is unpredictable and can lose details. This MCP uses deterministic rules to ensure the reduction is consistent and follows specific logic.

• 02

  Which AI clients can use this MCP?

  Any MCP-compatible client can use it, including Claude, Cursor, and Windsurf.

• 03

  Does this MCP work with my existing context?

  Yes, you can use it to analyze and compress existing text blocks to fit within your current context window.

• 04

  Can I see how much I saved?

  Yes, the get_optimization_report capability provides a structured overview of how effective the compression was.

• 05

  What kind of text does it compress?

  It works on redundant reasoning, repetitive descriptions, long file lists, and bulky code blocks.

• 06

  How does this capability ensure compression is deterministic?

  Unlike LLM summarization, this capability uses mathematical rules like Jaccard similarity and structural patterns to remove text, ensuring the technical meaning remains unchanged.

• 07

  What is the difference between analyze_verbosity and compress_text?

  The analyze_verbosity capability assesses the current redundancy and estimated savings, while compress_text actively applies the reduction rules to meet your specific token budget.

• 08

  Can I use this to clean up long file lists in my chat history?

  Yes, the compress_text capability includes a file list collapse rule that replaces long lists of changed files with a concise summary.

• 

  Context Window Optimizer AIコネクタ

  Optimizes LLM context windows by selecting the most relevant and recent information within token limits.

  表示
• 

  Context Window Economics Optimizer AIコネクタ

  Calculate the financial and performance impact of LLM context management strategies.

  表示
• 

  Context Window Eviction Planner AIコネクタ

  A deterministic engine to manage LLM context windows by calculating optimal message eviction.

  表示
• 

  LLM Context Window Budgeter AIコネクタ

  Monitor and predict LLM context window exhaustion with precision token forecasting.

  表示

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  Claude Context Window Budget Tracker AIコネクタ

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  Memory Context Priority Pruner AIコネクタ

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  Dynamic Context Window Packer AIコネクタ

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