Configures and optimizes Supabase as a production-ready vector and graph database backend for Mem0 OSS.
This skill provides a comprehensive framework for integrating Mem0 Open Source with Supabase, transforming it into a robust memory layer for AI agents. It automates the setup of PostgreSQL schemas with pgvector for semantic search, implements graph-based memory relationships, and enforces security through granular Row Level Security (RLS) policies. Whether you are migrating from the Mem0 Platform or building a self-hosted solution, this skill ensures your memory database is optimized with HNSW indexes, connection pooling via PgBouncer, and automated backup strategies.
Key Features
01Advanced Row Level Security (RLS) for multi-tenant and user-level isolation
02Optimized HNSW and GIN indexing for high-performance vector and text search
03Comprehensive migration tools for moving data from Mem0 Platform to self-hosted Supabase
04Automated PostgreSQL schema setup with pgvector extension support
05Production-ready connection pooling and automated backup strategy configuration
060 GitHub stars
Use Cases
01Building a secure, self-hosted long-term memory backend for AI agents
02Implementing multi-tenant memory isolation in a production SaaS application
03Scaling Mem0 vector storage using Supabase connection pooling and performance indexing
