A developer shares their solution to address Cursor AI's hallucination issues when generating React components with Supabase integration using a Model Context Protocol (MCP) server. The approach provides real-time schema information and type constraints to the AI, resulting in more accurate code generation and improved handling of database relationships and policies.
Create a Model Context Protocol (MCP) server that provides real-time Supabase schema information to Cursor AI for React component generation. The server should: 1. Maintain current database schema information including tables, relationships, and RLS policies 2. Provide type definitions for TypeScript 3. Handle foreign key relationships 4. Update automatically when schema changes 5. Integrate with existing React/TypeScript codebase 6. Support real-time schema validation during code generation
Implement a dedicated MCP server to provide real-time, accurate schema information to the AI
Implement automatic context updates that reflect codebase evolution
Include Row Level Security policies in the schema information provided to AI
Don't rely on static code snippets for database schema information
Don't let AI directly interpret database structures without proper context
Discussion about useful MCP (Model Control Protocol) servers to integrate with Cursor IDE beyond the standard command line and GitHub implementations. The post specifically mentions PostgreSQL and Redis servers for maintaining agent context, and seeks community recommendations for additional MCP servers not listed in the "awesome-mcp-servers" repository.
A comprehensive tutorial demonstrating how to build a custom MCP (Message Control Protocol) server to extend Cursor Composer's functionality. The author provides both a video walkthrough and open-source repository to help developers implement practical and advanced features beyond the basic examples in the official documentation.
A developer shares their 4-month experience using Cursor Pro, detailing specific workflow optimizations and challenges. The post covers successful strategies like .cursorrules optimization, debug statement usage, and context management, while also highlighting limitations with less common technologies like Firebase/TypeScript, SwiftUI, and Svelte 5.
A user shares a valuable tip for improving code generation quality in Cursor AI by explicitly requesting it to ask clarifying questions. The post highlights how adding a simple prompt rule can prevent hallucinated code and lead to more accurate, contextually appropriate code generation through interactive refinement.
A critical discussion about the misuse and misunderstanding of the Cursor AI coding assistant. The post emphasizes that users should treat Cursor as a helpful tool rather than a complete replacement for human developers, drawing an analogy to calculator usage.