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Supabase Vector MCP Server for Cursor 7 tools — connect in under 2 minutes

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Cursor is an AI-first code editor built on VS Code that integrates LLM-powered coding assistance directly into the development workflow. Its Agent mode enables autonomous multi-step coding tasks, and MCP support lets agents access external data sources and APIs during code generation.

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Classic Setup·json
{
  "mcpServers": {
    "supabase-vector": {
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}
Supabase Vector
Fully ManagedVinkius Servers
60%Token savings
High SecurityEnterprise-grade
IAMAccess control
EU AI ActCompliant
DLPData protection
V8 IsolateSandboxed
Ed25519Audit chain
<40msKill switch
Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Supabase Vector MCP Server

Integrate the powerful AI-native PostgreSQL extensions of Supabase Vector straight into your conversational LLM workflows. By authenticating your environment natively with the service_role key, your AI assistant bypasses row-level security constraints to operate as an unrestricted database administrator. Perform advanced similarity searches using the pgvector extension, parse and manipulate multi-dimensional embeddings, and execute foundational CRUD operations via simple natural language commands. Streamline RAG (Retrieval-Augmented Generation) setups and semantic engineering directly, avoiding the need for external dashboards or manual SQL querying.

Cursor's Agent mode turns Supabase Vector into an in-editor superpower. Ask Cursor to generate code using live data from Supabase Vector and it fetches, processes, and writes. all in a single agentic loop. 7 tools appear alongside file editing and terminal access, creating a unified development environment grounded in real-time information.

What you can do

  • Semantic Vector Matching — Seamlessly query unstructured contextual similarities performing embedding comparisons by executing match_vectors utilizing custom postgres RPC parameters locally.
  • Database Structural Interaction — Systematically browse schema availability utilizing list_tables and extract specific data arrays effortlessly through query_table_rows.
  • Content State Manipulations — Seamlessly orchestrate data inputs invoking insert_table_rows or explicitly clear legacy assignments logically mapping identifiers with delete_table_rows.
  • Custom Functional Logic — Launch sophisticated PL/pgSQL algorithms statically configured in your Supabase backend directly with call_postgres_function.

The Supabase Vector MCP Server exposes 7 tools through the Vinkius. Connect it to Cursor in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Supabase Vector to Cursor via MCP

Follow these steps to integrate the Supabase Vector MCP Server with Cursor.

01

Open MCP Settings

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

02

Add the server config

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

03

Save the file

Cursor will automatically detect the new MCP server

04

Start using Supabase Vector

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

Why Use Cursor with the Supabase Vector MCP Server

Cursor AI Code Editor provides unique advantages when paired with Supabase Vector through the Model Context Protocol.

01

Agent mode turns Cursor into an autonomous coding assistant that can read files, run commands, and call MCP tools without switching context

02

Cursor's Composer feature can generate entire files using real-time data fetched through MCP. no copy-pasting from external dashboards

03

MCP tools appear alongside built-in tools like file reading and terminal access, creating a unified agentic environment

04

VS Code extension compatibility means your existing workflow, keybindings, and extensions all work alongside MCP tools

Supabase Vector + Cursor Use Cases

Practical scenarios where Cursor combined with the Supabase Vector MCP Server delivers measurable value.

01

Code generation with live data: ask Cursor to generate a security report module using live DNS and subdomain data fetched through MCP

02

Automated documentation: have Cursor query your API's tool schemas and generate TypeScript interfaces or OpenAPI specs automatically

03

Infrastructure-as-code: Cursor can fetch domain configurations and generate corresponding Terraform or CloudFormation templates

04

Test scaffolding: ask Cursor to pull real API responses via MCP and generate unit test fixtures from actual data

Supabase Vector MCP Tools for Cursor (7)

These 7 tools become available when you connect Supabase Vector to Cursor via MCP:

01

call_postgres_function

Calls a custom Postgres function (RPC) with parameters

02

delete_table_rows

This action is irreversible. Deletes rows from a table based on a column value

03

get_table_row

Retrieves a specific row by matching a column value

04

insert_table_rows

Provide a JSON array of row objects. Inserts new rows into a specific table

05

list_tables

Lists all tables in the Supabase project

06

match_vectors

Requires a valid RPC function name and an embedding array. Performs a vector similarity search via Postgres RPC

07

query_table_rows

Provide table name and optional select/limit. Queries rows from a specific table

Example Prompts for Supabase Vector in Cursor

Ready-to-use prompts you can give your Cursor agent to start working with Supabase Vector immediately.

01

"Using the 'match_docs' vector RPC natively, analyze my embedding representation returning seamlessly the top 5 matches."

02

"Browse my schema directly to identify active vector tables and delete any legacy testing embeddings from 'test_docs' securely."

03

"Insert a new embedding natively calling `insert_table_rows` with the corresponding context efficiently."

Troubleshooting Supabase Vector MCP Server with Cursor

Common issues when connecting Supabase Vector to Cursor through the Vinkius, and how to resolve them.

01

Tools not appearing in Cursor

Ensure you are in Agent mode (not Ask mode). MCP tools only work in Agent mode.
02

Server shows as disconnected

Check Settings → Features → MCP and verify the server status. Try clicking the refresh button.

Supabase Vector + Cursor FAQ

Common questions about integrating Supabase Vector MCP Server with Cursor.

01

What is Agent mode and why does it matter for MCP?

Agent mode is Cursor's autonomous execution mode where the AI can perform multi-step tasks: reading files, editing code, running terminal commands, and calling MCP tools. Without Agent mode, Cursor operates in a simpler ask-and-answer mode that doesn't support tool calling. Always ensure you're in Agent mode when working with MCP servers.
02

Where does Cursor store MCP configuration?

Cursor looks for MCP server configurations in a mcp.json file. You can configure servers at the project level (.cursor/mcp.json in your project root) or globally (~/.cursor/mcp.json). Project-level configs take precedence.
03

Can Cursor use MCP tools in inline edits?

No. MCP tools are only available in Agent mode through the chat panel. Inline completions and Tab suggestions do not trigger MCP tool calls. This is by design. tool calls require user visibility and approval.
04

How do I verify MCP tools are loaded?

Open Settings → Features → MCP and look for your server name. A green indicator means the server is connected. You can also check Agent mode's available tools by clicking the tools dropdown in the chat panel.

Connect Supabase Vector to Cursor

Get your token, paste the configuration, and start using 7 tools in under 2 minutes. No API key management needed.