Conecte Supabase Vector ao ChatGPT, Claude e Gemini

• 01 / 02Como depurar similaridade
• 02 / 02Como executar funções Postgres

Dia mais rápido

769ms

Dia mais lento

1194ms

Tendência de 14 dias

Estável-1%

Supabase Vector Connector

Tudo pronto. Escolha seu cliente MCP e siga as instruções de configuração.

Link do conectorhttps://edge.vinkius.com/vk_preview_r2cwX4M1GouGmm6VnqY7CUQyTiHKovu2fp0L81jN/mcpCopiar

Claude Desktop

Siga os passos abaixo para conectar em segundos.

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.

Configuração · claude_desktop_config.jsonCopiar

{
  "mcpServers": {
    "supabase-vector-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_r2cwX4M1GouGmm6VnqY7CUQyTiHKovu2fp0L81jN/mcp"
    }
  }
}

• Claude
• ChatGPT
• Cursor
• VS Code
• Windsurf
• Claude Code
• JetBrains
• Cline

Instruções passo a passo para cada cliente estão no guia. Como conectar

Configuração guiada para o Claude? Configurar Supabase Vector no Claude e outras IAs

Veja todos os clientes de IA com quem este connector funciona ↑

• 01

  Engenheiros de IA e Dados

  Iteram rapidamente em arquiteturas de embeddings e testam métricas de distância sem plataformas externas.

• 02

  Administradores de PostgreSQL

  Diagnosticam a precisão semântica diretamente via prompt, ajustando valores de forma conversacional.

• 03

  Desenvolvedores Backend

  Avaliam infraestruturas vetoriais e implementações de RAG diretamente no ambiente de trabalho.

• 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.

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