AI Memory Cost AnalyzerをChatGPTとClaudeに接続

最速日

655ms

最遅日

1079ms

14日間の傾向

遅延傾向+12%

AI Memory Cost Analyzer 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_4MaqXgJc5713NJFvD3nfrG7ypHzOyFpIRGwcjqw6/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 — AI Memory Cost Analyzer capabilities are ready to use.

設定 · claude_desktop_config.jsonコピー

{
  "mcpServers": {
    "ai-memory-cost-analyzer-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_4MaqXgJc5713NJFvD3nfrG7ypHzOyFpIRGwcjqw6/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？ AI Memory Cost Analyzer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エンジニア

  LLMの推論コストやメモリ管理の最適化を直接行う開発者。

• 02

  システムアーキテクト

  システム全体の費用対効果を考慮し、最適なデータフローとメモリ構造を設計する設計者。

• 03

  プロダクトマネージャー

  AI機能の導入によるビジネスインパクトを最大化し、コストと機能のバランスを取る責任者。

• 01

  Is this for general AI cost tracking?

  No. This MCP focuses specifically on the economics of AI conversation memory. It helps you model the costs related to context window usage, storage, and retrieval overhead.

• 02

  What kind of costs can I calculate?

  You can calculate three main types of costs: the runtime cost of the conversation, the cost of persistent storage, and the cost of retrieving that stored data.

• 03

  Do I need to know my token pricing beforehand?

  Yes, the capabilities require you to input the token price and usage volume to generate an accurate cost estimate.

• 04

  Can I use this to compare different memory methods?

  Absolutely. You can use the simulation capabilities to compare methods like full context versus summarization, showing you potential percentage savings.

• 05

  How can I reduce my LLM inference costs?

  You can use analyze_optimization_opportunities to compare your current strategy against alternatives like summarization or pruning to identify potential savings.

• 06

  Does this capability account for vector database costs?

  Yes, by using calculate_storage_and_retrieval_overhead, you can estimate the persistent costs of maintaining history in different storage tiers and the cost of retrieval queries.

• 07

  What is the difference between summarization and pruning?

  Summarization compresses older turns into a condensed summary to save tokens, while pruning drops the oldest tokens entirely once a window limit is reached.

• 

  Token Cost Estimator AIコネクタ

  Calculate precise LLM usage costs and optimization targets.

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• 

  AI SaaS Token Economics Engine AIコネクタ

  Analyze token consumption, feature efficiency, and tier-based costs for AI SaaS platforms.

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• 

  AI Context Window Economics AIコネクタ

  Analyze the financial impact of context window scaling on LLM inference costs.

  表示
• 

  LLM API Cost Estimator AIコネクタ

  Calculate exact API costs and track session budgets for LLM workflows.

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