Supabase AI Agent Server with RAG & Multi-Tenant CRUD

This n8n workflow creates a robust Supabase-powered server for AI agents, integrating Retrieval-Augmented Generation (RAG) with OpenAI embeddings and Supabase vector search. It enables context-aware responses by retrieving relevant knowledge from vector stores, while supporting full CRUD operations on tables like agent_messages, agent_tasks, agent_status, and agent_knowledge. Multi-tenancy is achieved through dynamic table names and webhook paths, ensuring data isolation per user or organization