Memgraph's AI Toolkit, featuring SQL2Graph and Unstructured2Graph, addresses the challenge of context engineering for AI teams by converting structured and unstructured data into graph-ready formats, thus facilitating the development of Graph-based Retrieval-Augmented Generation (GraphRAG) systems. SQL2Graph automates the transformation of SQL schemas from databases like MySQL and PostgreSQL into property graphs using Memgraph’s Hypothetical Graph Model (HyGM), allowing for either automatic or incremental migration with validation. Meanwhile, Unstructured2Graph efficiently converts unstructured documents such as PDFs and DOCx files into connected knowledge graphs, leveraging LLM-based entity extraction through LightRAG integration to link document nodes and extracted entities. Together, these tools simplify the process of structuring data for intelligent systems, enabling developers to more easily build AI applications that can retrieve and reason over interconnected data.