Supabase Vector Connector for AI agents.

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

Executing deletetablerows 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.

7 live capabilities

Manage pgvector embeddings and relational data through a conversational interface.

Live agent request Supabase Vector / Connector

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AI Agent

Why people use Supabase Vector

Supabase Vector for pgvector Semantic Search

This Connector puts your entire Supabase Vector instance into the hands of your AI client. You can ask your agent to list your tables, query specific rows, or run similarity searches just by describing what you want to find. It turns a multi-step database management workflow into a single conversation, giving you a much faster way to iterate on your RAG stack.

What Vinkius changes

That you get a conversational interface for your entire Supabase Vector database.

Use it from Claude, ChatGPT, Cursor or another AI client you already have.

One account · 5,900+ Connectors

Real-world use case 01

Debugging RAG

An engineer asks the agent to find the top 3 matches for a query and then uses call_postgres_function to trigger a review.
Real-world use case 02

Data Cleanup

A developer tells the agent to find all rows in 'test_embeddings' and use delete_table_rows to clear out the junk.
Real-world use case 03

Schema Exploration

A new team member asks the agent to list all tables and then query the 'documents' table to see the current structure.

Complete set · 7capabilities

The complete Supabase Vector capability set.

These are the exact actions your AI can choose when you ask it to work with Supabase Vector.

Capability set01 / 02

01—04

4 capabilities in this set.

Part of 7 available through Supabase Vector.

01 Capability
Delete table rows
Removes specific rows from a table based on a column value.
02 Capability
Get table row
Fetches a single row from a table when you provide a specific column value.
03 Capability
Insert table rows
Adds new data to a table using a JSON array of objects.
04 Capability
List tables
Shows a list of all available tables in your Supabase project.

Capability set02 / 02

05—07

3 capabilities in this set.

Part of 7 available through Supabase Vector.

05 Capability
Match vectors
Runs a similarity search using a vector RPC and an embedding array.
06 Capability
Query table rows
Pulls rows from a table with optional filters or limits.
07 Capability
Call postgres function
Executes a custom Postgres RPC function with your specific parameters.

Set up in minutes

One URL. Then ask Supabase Vector to work.

Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use Supabase Vector from the conversation.

Choose your client

Live preview

Advanced clients IDE · CLI

Claude · Web + desktop

Official guide ↗

Connector URL · ready to paste

Streamable HTTP

https://edge.vinkius.com/vk_preview_r2cwX4M1GouGmm6VnqY7CUQyTiHKovu2fp0L81jN/mcp

Step 01

Open Connectors

In Claude Web or Claude Desktop, open Settings and choose Connectors.
Step 02

Add the URL

Choose Add custom connector, name it Supabase Vector, and paste the URL above.
Step 03

Turn it on in chat

Select +, open Connectors, and enable Supabase Vector for the conversation.

ChatGPT · Web + desktop

Official guide ↗

Connector URL · ready to paste

Streamable HTTP

https://edge.vinkius.com/vk_preview_r2cwX4M1GouGmm6VnqY7CUQyTiHKovu2fp0L81jN/mcp

Step 01

Open MCP settings

On desktop, open Settings and MCP servers. On web, open your workspace app or connector settings.
Step 02

Add the URL

Choose Add server with Streamable HTTP, or create a custom MCP app, then paste the Supabase Vector URL.
Step 03

Save and start

Save the connection and enable Supabase Vector in your conversation. Desktop may ask you to restart once.

Cursor · IDE configuration

Official guide ↗

Advanced setup

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

Step 01

Open MCP Settings

Press Cmd+Shift+P (macOS) or Ctrl+Shift+P (Windows/Linux) → search "MCP Settings"
Step 02

Add the server config

Paste the JSON configuration above into the mcp.json file that opens
Step 03

Save the file

Cursor will automatically detect the new Connector
Step 04

Start using Supabase Vector

Open Agent mode in chat and ask: "Using Supabase Vector, help me...". 7 tools available

VS Code Copilot · IDE configuration

Official guide ↗

Advanced setup

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

Step 01

Create MCP config

Create a .vscode/mcp.json file in your project root
Step 02

Add the server config

Paste the JSON configuration above
Step 03

Enable Agent mode

Open GitHub Copilot Chat and switch to Agent mode using the dropdown
Step 04

Start using Supabase Vector

Ask Copilot: "Using Supabase Vector, help me...". 7 tools available

Windsurf · IDE configuration

Official guide ↗

Advanced setup

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

Step 01

Open MCP Settings

Go to Settings → MCP Configuration or press Cmd+Shift+P and search "MCP"
Step 02

Add the server

Paste the JSON configuration above into mcp_config.json
Step 03

Save and reload

Windsurf will detect the new server automatically
Step 04

Start using Supabase Vector

Open Cascade and ask: "Using Supabase Vector, help me...". 7 tools available

Cline · IDE configuration

Official guide ↗

Advanced setup

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

Step 01

Open Cline MCP Settings

Click the Connectors icon in the Cline sidebar panel
Step 02

Add remote server

Click "Add Connector" and paste the configuration above
Step 03

Enable the server

Toggle the server switch to ON
Step 04

Start using Supabase Vector

Ask Cline: "Using Supabase Vector, help me...". 7 tools available

Claude Code · Terminal command

Official guide ↗

Advanced setup

claude mcp add supabase-vector --transport http "https://edge.vinkius.com/vk_preview_r2cwX4M1GouGmm6VnqY7CUQyTiHKovu2fp0L81jN/mcp"

Step 01

Install Claude Code

Run npm install -g @anthropic-ai/claude-code if not already installed
Step 02

Add the Connector

Run the command above in your terminal
Step 03

Verify the connection

Run claude mcp to list connected servers, or type /mcp inside a session
Step 04

Start using Supabase Vector

Ask Claude: "Using Supabase Vector, show me...". 7 tools are ready

Where the request belongs

Work Supabase Vector can move forward.

Built around the request

This is for the engineer who is tired of copy-pasting IDs between a spreadsheet and a SQL console, or the data scientist who needs to see if their embeddings actually make sense without building a full frontend.

AI Engineer

Testing embedding models and RAG accuracy without leaving the chat window.

Database Administrator

Managing schema changes and data integrity for vector-enabled apps.

Backend Developer

Quickly debugging production data and verifying RPC functions.

Build the capability set

Each Connector adds new actions and data without changing how you work.

Browse Connectors

01 6 capabilities

LanceDB (Serverless Vector DB)

Manage vectorized data via LanceDB. perform similarity searches, create tables, and manage multi-modal embeddings.

View Connector

02 6 capabilities

pgvector (Vector Database)

Run vector similarity searches, manage embedding tables, and build AI-powered retrieval pipelines. all directly inside your existing PostgreSQL database.

View Connector

03 6 capabilities

MyScale (SQL Vector Database API)

Manage MyScale vector databases via SQL. execute queries, perform vector searches, and manage indices directly from any AI agent.

View Connector

04 7 capabilities

Qdrant

Empower your AI to interact directly with your Qdrant vector database. query clusters, perform similarity searches, and manage collections effortlessly.

View Connector

05 7 capabilities

Weaviate

Search and manage vector data on Weaviate. the AI-native database for building production-grade AI applications.

View Connector

06 7 capabilities

Couchbase (Vector & NoSQL)

Manage vector search and NoSQL via Couchbase. execute N1QL queries, perform KNN vector searches, and audit documents directly from any AI agent.

View Connector

Bring your own AI

Change the model, client or framework. Keep Supabase Vector connected.

Claude
ChatGPT
Gemini
Cursor
VS Code
Windsurf
ZCode
Cline
Zed
Continue
Kiro
Roo Code
Zencoder
Goose
Void
Augment Code
Amp
Qodo
Tabnine
Pieces
Sourcegraph Cody
JetBrains
Warp
Amazon Q
Antigravity
BoltAI
Raycast
Jan
LM Studio
AnythingLLM
Open WebUI
Msty
Cherry Studio
LibreChat
TypingMind
Chorus
5ire
n8n
LangChain
LlamaIndex
CrewAI
Vercel AI SDK

Before you connect

Questions about Supabase Vector.

The practical details behind the request, access and result.

Can the Supabase Vector MCP help me build a RAG system?

Yes, it connects your AI client directly to your vector database, making it easy to perform similarity searches and retrieve relevant context for your agent.

Does the Supabase Vector MCP allow me to delete data?

It can delete specific rows from your tables based on a value you provide, which is great for cleaning up test data or removing old records.

Can I run my own custom functions with the Supabase Vector MCP?

Yes, you can call any Postgres RPC functions you've already configured in your Supabase backend directly through your AI client.

Is this Connector only for vector searches?

No, while it's great for pgvector similarity searches, it also lets your agent perform standard relational queries and manage your regular database tables.

Do I need to know SQL to use the Supabase Vector MCP?

You don't need to write SQL; you just tell your AI client what you want to do in plain English, and it uses the Connector capabilities to execute the commands.

How does the Supabase Vector MCP handle my database security?

It uses your service role key to operate as an administrator, so it can bypass row-level security to perform the actions you request.

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.

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.

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.

One connection away

Give your agent a direct line to Supabase Vector.

Connect Supabase Vector once. Keep it beside 5,900+ managed Connectors when the next task needs more.

Explore every Connector No credit card required · Free tier available

Supabase Vector for pgvector Semantic Search

That you get a conversational interface for your entire Supabase Vector database.

Debugging RAG

Data Cleanup

Schema Exploration

Delete table rows

Get table row

Insert table rows

List tables

Match vectors

Query table rows

Call postgres function

Open Connectors

Add the URL

Turn it on in chat

Open MCP settings

Add the URL

Save and start

Open MCP Settings

Add the server config

Save the file

Start using Supabase Vector

Create MCP config

Add the server config

Enable Agent mode

Start using Supabase Vector

Open MCP Settings

Add the server

Save and reload

Start using Supabase Vector

Open Cline MCP Settings

Add remote server

Enable the server

Start using Supabase Vector

Install Claude Code

Add the Connector

Verify the connection

Start using Supabase Vector

AI Engineer

Database Administrator

Backend Developer

LanceDB (Serverless Vector DB)

pgvector (Vector Database)

MyScale (SQL Vector Database API)

Qdrant

Weaviate

Couchbase (Vector & NoSQL)

Give your agent a direct line to Supabase Vector.