Integrations
Uses .env files for securely managing Supabase credentials and configuration settings for the MCP server.
Supports containerized deployment with Docker and Docker Compose, allowing for easy setup, management and troubleshooting of the MCP server environment.
Utilizes Pydantic for type-safe request/response handling, ensuring data validation and consistent interactions with the Supabase database.
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
- Clone the repository:
- Create a
.env
file with your Supabase credentials:
- Build and start the container:
The server will be available at http://localhost:8000
.
Docker Management Commands
Troubleshooting Docker Issues
- If the container fails to start:Copy
- If you get port conflicts:Copy
- If environment variables aren't loading:Copy
Configuring MCP in Your AI IDE
General Configuration Steps
- Open your AI IDE's settings/preferences
- Navigate to the MCP or AI settings section
- Add a new MCP server with the following configuration:
IDE-Specific Instructions
Cursor
- Open Settings (⌘, or Ctrl+,)
- Go to "AI" section
- Under "MCP Servers", click "Add Server"
- Use the configuration above
- Restart Cursor to apply changes
VS Code with AI Extensions
- Open Command Palette (⌘⇧P or Ctrl+Shift+P)
- Search for "MCP" or "AI Settings"
- Add new MCP server configuration
- Use the configuration above
- Reload VS Code window
JetBrains IDEs with AI Plugins
- Open Settings (⌘, or Ctrl+Alt+S)
- Navigate to "Tools" → "AI" → "MCP Servers"
- Click "+" to add new server
- Use the configuration above
- Restart IDE to apply changes
Verifying MCP Connection
- Check your IDE's status bar for MCP server status
- Look for a green indicator or "MCP Connected" message
- Try using AI features that require database access
- Check Docker logs for any connection issues:Copy
Usage
- Start the MCP server:
- 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
- Fork the repository
- Create a feature branch
- Commit your changes
- Push to the branch
- Create a Pull Request
License
MIT
This server cannot be installed
A Model Context Protocol server that enables AI tools to interact with Supabase databases, providing tools for reading, creating, updating, and deleting records in Supabase tables.
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