Memory Context Priority PrunerをAIに接続

最速日

557ms

最遅日

831ms

14日間の傾向

改善傾向-15%

Memory Context Priority Pruner 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_wn6QQ6MBDELDQuy390LTPIrEYUANWateQNUsl4sW/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 — Memory Context Priority Pruner capabilities are ready to use.

設定 · claude_desktop_config.jsonコピー

{
  "mcpServers": {
    "memory-context-priority-pruner-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_wn6QQ6MBDELDQuy390LTPIrEYUANWateQNUsl4sW/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？ Memory Context Priority Pruner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

  AI Engineers

  They hand off complex conversation histories to agents that need to remain performant.

• 02

  Prompt Engineers

  They use it to ensure system instructions aren't lost during long sessions.

• 03

  Workflow Automators

  They manage token costs and window limits for automated agentic tasks.

• 01

  Will this delete my system instructions?

  No. The MCP treats system instructions and the first user message as immutable, so they are never pruned.

• 02

  How does it decide which messages to remove?

  It uses relevance scores for middle-tier messages, keeping the most important content that fits your token budget.

• 03

  Can I use this with Cursor or Windsurf?

  Yes. This MCP works with any MCP-compatible client, including Cursor, Windsurf, and VS Code.

• 04

  Does it keep my recent messages?

  Yes. It maintains a protected buffer of recent messages to ensure the immediate context remains intact.

• 05

  How do I know how many tokens I'll save?

  You can use the predict_pruning_impact capability to simulate a strategy and see the expected token reduction before executing it.

• 06

  What makes the pruning process deterministic?

  The process follows strict, unchangeable rules: it always preserves system messages and the first user message, protects a recent buffer of N messages, and then selects middle messages based on their relevance score until the token budget is reached.

• 07

  How can I see how much space my current conversation is using?

  You can use the analyze_context_density capability. It will break down your message list into immutable, buffer, and prunable token counts.

• 08

  Can I simulate a pruning run before actually deleting messages?

  Yes, the predict_pruning_impact capability allows you to estimate how many tokens will be saved and what information will remain without modifying your actual message list.

• 

  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
• 

  Dynamic Context Window Packer AIコネクタ

  Optimally packs retrieved documents into LLM context windows using a greedy knapsack algorithm.

  表示
• 

  Context Window Utilization Analyzer AIコネクタ

  A deterministic tool for tracking and predicting AI context window exhaustion.

  表示
• 

  Claude Verbosity Optimizer AIコネクタ

  A deterministic engine to detect and compress verbose LLM outputs to preserve context window budget.

  表示

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  Memory Context Window Pruner AIコネクタ

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  Context Window Eviction Planner AIコネクタ

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  Context Window Economics Optimizer AIコネクタ

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

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• 

  Agent Context Window Manager AIコネクタ

  Deterministic token tracking and context optimization for long-running AI conversations.

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