Allows querying of the feature_suggestions table in a Supabase database, with optional limits on the number of records returned.
Supabase MCP Server
This is a Model Context Protocol (MCP) server that connects to Supabase and allows you to query the feature_suggestions table.
Prerequisites
Node.js (v16 or higher)
npm
Supabase project with credentials
Setup
Make sure your
.env
file contains the following Supabase credentials:SUPABASE_URL=your_supabase_url SUPABASE_ANON_KEY=your_supabase_anon_keyInstall the required dependencies:
npm install
Running the Server
Run the MCP server using:
Or use the npm script:
Connecting to AI Tools
Cursor
Open Cursor and navigate to Cursor Settings.
Under the Features tab, tap + Add new MCP server under the MCP Servers section.
Enter the following details:
Name: Supabase
Type: command
Command:
npx tsx /path/to/mcp-server.ts
You should see a green active status after the server is successfully connected.
Claude Desktop
Open Claude desktop and navigate to Settings.
Under the Developer tab, tap Edit Config to open the configuration file.
Add the following configuration:
{ "mcpServers": { "supabase": { "command": "npx", "args": ["tsx", "/path/to/mcp-server.ts"] } } }Save the configuration file and restart Claude desktop.
Available Tools
query_feature_suggestions
Query the feature_suggestions table in your Supabase database.
Parameters:
limit
(number, optional): Maximum number of records to return (default: 100)
Example usage in AI tool:
Or with a limit:
Troubleshooting
If you encounter connection issues, make sure your Supabase credentials are correct.
Check the console output for any error messages.
Ensure that the feature_suggestions table exists in your Supabase database.
This server cannot be installed
remote-capable server
The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.
A Model Context Protocol server that enables querying feature suggestions from a Supabase database, allowing AI tools like Cursor and Claude to access and display feature request data.
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