Supabase VectorをChatGPT、Claude、Geminiに接続

• 01 / 02類似性検索のデバッグ方法
• 02 / 02Postgres関数の実行方法

最速日

769ms

最遅日

1194ms

14日間の傾向

安定-1%

Supabase Vector 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_r2cwX4M1GouGmm6VnqY7CUQyTiHKovu2fp0L81jN/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 — Supabase Vector capabilities are ready to use.

設定 · claude_desktop_config.jsonコピー

{
  "mcpServers": {
    "supabase-vector-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_r2cwX4M1GouGmm6VnqY7CUQyTiHKovu2fp0L81jN/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？ Supabase Vector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・データエンジニア

  外部プラットフォームを開くことなく、埋め込みモデルや距離指標のテストを行い、埋め込みアーキテクチャを迅速に反復開発できます。

• 02

  PostgreSQLデータベース管理者

  プロンプトから直接セマンティックな精度を診断し、対話的な配列操作を通じて入力を構成できます。

• 03

  バックエンド開発者

  作業中のワークスペースで直接、ベクトルデータベースやRAGデプロイメントのデバッグを行い、インフラの検証を迅速化できます。

• 01

  How does the MCP handle security?

  The MCP uses your Supabase service role key, which allows the agent to bypass row-level security to perform administrative tasks.

• 02

  What is required to use the vector search capability?

  To use match_vectors, you must provide a valid RPC function name and a corresponding embedding array.

• 03

  Can I delete data using this MCP?

  Yes, you can use delete_table_rows to remove data, but be aware that this action is irreversible.

• 04

  Which AI clients can use this MCP?

  Any MCP-compatible client like Claude, Cursor, Windsurf, or VS Code can use this capability.

• 05

  Do I need to write SQL to use this?

  No, you can perform most operations like inserting rows or querying tables using natural language commands.

• 06

  Are embedding arrays processed efficiently during intensive vector similarity matching?

  The integration specifically manages large semantic arrays seamlessly by calling lightweight Postgres RPC configurations locally natively internally securely.

• 07

  How is risk managed securely when manipulating and clearing root analytical vectors?

  Executing delete_table_rows operates systematically relying inherently on exactly structured string conditions implicitly naturally precisely eliminating ambiguity securely effectively actively strictly smoothly securely precisely correctly reliably locally dynamically successfully effortlessly intelligently gracefully elegantly safely accurately directly comprehensively natively.

• 08

  Which distance metrics does the vector search support?

  pgvector supports cosine similarity, inner product, and L2 (Euclidean) distance. The metric used depends on how your RPC function and index are configured in PostgreSQL. the AI passes arguments accordingly.

• 

  Marqo AI (Vector Search & Embeddings) AIコネクタ

  Manage semantic search via Marqo — execute tensor queries, index JSON documents, and audit vector indices.

  表示
• 

  Lucidworks Fusion (AI Search & Discovery) AIコネクタ

  Manage AI-powered search via Lucidworks Fusion — execute semantic queries, index documents, and monitor ML tra

  表示
• 

  Redis Vector AIコネクタ

  Equip your AI to autonomously manage embeddings, run KNN similarity searches, and administrate vector indexes

  表示
• 

  Typesense Vector Search AIコネクタ

  Automate vector similarity searches via Typesense — index documents, manage collections, and execute semantic

  表示

おすすめ

• 

  Chroma (Vector DB) AIコネクタ

  Manage vector embeddings via Chroma — list collections, query embeddings, and audit document counts directly f

  表示
• 

  MongoDB Atlas Vector Search AIコネクタ

  Manage vector storage via MongoDB Atlas — perform similarity searches, query MQL documents, and audit collecti

  表示
• 

  Elasticsearch Vector AIコネクタ

  Empower vector search via Elasticsearch — perform dense vector kNN searches, handle index mappings, and index

  表示
• 

  Vertex AI Vector Search AIコネクタ

  Bring Google's massive vector matching power to your AI agent. Search billions of semantic embeddings and admi

  表示