Vector Index Recall EstimatorをAIに接続

最速日

542ms

最遅日

803ms

14日間の傾向

安定0%

Vector Index Estimator 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_N33Tt9r0kNlk9h9CQjDLut4LHlCfuA7wPCcdfONP/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 — Vector Index Estimator capabilities are ready to use.

設定 · claude_desktop_config.jsonコピー

{
  "mcpServers": {
    "vector-index-recall-estimator-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_N33Tt9r0kNlk9h9CQjDLut4LHlCfuA7wPCcdfONP/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？ Vector Index Estimator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

  機械学習エンジニア

  ベクトル検索モデルの精度と推論速度の最適化を行う担当者。

• 02

  データエンジニア

  大規模なベクトルデータの保存と検索のためのインフラ設計を行う担当者。

• 03

  AIシステムアーキテクト

  検索性能とハードウェアコストのトレードオフを管理する設計者。

• 01

  How does this MCP help with vector database scaling?

  It allows you to estimate the memory footprint and search performance for different scales, helping you plan your hardware needs before deployment.

• 02

  Which algorithms are supported?

  The MCP provides performance modeling for HNSW and IVF algorithms.

• 03

  Can I use this to find the best efSearch value?

  Yes, you can use the parameter recommendation capability to find optimal ranges for values like efSearch based on your target recall.

• 04

  Do I need to host the MCP myself?

  No, Vinkius hosts and manages the MCP, so you just connect your client and start using the capabilities.

• 05

  What kind of data do I need to provide for memory estimates?

  You need to provide the vector count, the number of dimensions, and the precision tier you are using.

• 06

  What algorithms are supported?

  The server supports HNSW (Hierarchical Navigable Small World) and IVF (Inverted File Index) algorithms.

• 07

  How can I estimate the RAM needed for my index?

  Use the calculate_memory_usage capability. You will need to provide the total vector count, dimensions per vector, and the precision tier (float32, float16, or int8).

• 08

  Can I get parameter suggestions for a specific recall target?

  Yes, the get_parameter_recommendations capability provides suggested ranges for parameters like efSearch or nprobe to help you reach your target recall percentage.

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