Supabase MCP Server

A Model Context Protocol (MCP) server that enables AI tools to interact with Supabase databases. This server provides tools for reading, creating, updating, and deleting records in Supabase tables.

Features

• Read rows from any Supabase table with filtering and column selection

• Create single or multiple records in tables

• Update records based on filter conditions

• Delete records based on filter conditions

• Comprehensive tool descriptions for AI model understanding

• Type-safe request/response handling with Pydantic

• Docker support for easy deployment

Prerequisites

• Python 3.9+

• Docker and Docker Compose

• Supabase project with service role key

• FastMCP-compatible AI IDE

Installation

1. Clone the repository:

2. Create a .env file with your Supabase credentials:

3. Build and start the container:

The server will be available at http://localhost:8000.

Docker Management Commands

Troubleshooting Docker Issues

1. If the container fails to start:

   # Check logs docker-compose logs -f # Check container status docker-compose ps # Remove and rebuild docker-compose down docker-compose up --build

2. If you get port conflicts:

   # Stop any existing containers using port 8000 docker-compose down # Or modify the port in docker-compose.yml # ports: # - "8000:8000" # Change the first number to an available port

3. If environment variables aren't loading:

   # Verify .env file exists and has correct values cat .env # Check environment variables in container docker-compose exec mcp-server env

Configuring MCP in Your AI IDE

General Configuration Steps

1. Open your AI IDE's settings/preferences

2. Navigate to the MCP or AI settings section

3. Add a new MCP server with the following configuration:

IDE-Specific Instructions

Cursor

1. Open Settings (⌘, or Ctrl+,)

2. Go to "AI" section

3. Under "MCP Servers", click "Add Server"

4. Use the configuration above

5. Restart Cursor to apply changes

VS Code with AI Extensions

1. Open Command Palette (⌘⇧P or Ctrl+Shift+P)

2. Search for "MCP" or "AI Settings"

3. Add new MCP server configuration

4. Use the configuration above

5. Reload VS Code window

JetBrains IDEs with AI Plugins

1. Open Settings (⌘, or Ctrl+Alt+S)

2. Navigate to "Tools" → "AI" → "MCP Servers"

3. Click "+" to add new server

4. Use the configuration above

5. Restart IDE to apply changes

Verifying MCP Connection

1. Check your IDE's status bar for MCP server status

2. Look for a green indicator or "MCP Connected" message

3. Try using AI features that require database access

4. Check Docker logs for any connection issues:

   docker-compose logs -f

Usage

1. Start the MCP server:

2. Configure your AI tool to use the MCP server:

Available Tools

read_rows

Read rows from a Supabase table with optional filtering and column selection.

Example usage:

create_records

Create one or more records in a Supabase table.

Example usage:

update_records

Update records in a Supabase table based on filter conditions.

Example usage:

delete_records

Delete records from a Supabase table based on filter conditions.

Example usage:

Security Considerations

• Always use the service role key in a secure environment

• Never expose the service role key in client-side code

• Use appropriate row-level security policies in Supabase

• Consider implementing rate limiting for production use

Contributing

1. Fork the repository

2. Create a feature branch

3. Commit your changes

4. Push to the branch

5. Create a Pull Request

License

MIT