The Gen AI Toolbox for Databases has been launched in collaboration with LangChain, now including a Neo4j integration. This integration brings knowledge graph capabilities to users, expanding the functionality of database management and Gen AI applications. Agentic architectures differ from traditional retrieval-augmented generation (RAG) approaches, where the LLM is equipped with tools for information retrieval and taking action on behalf of the user. The toolbox enables developers to build agentic applications that integrate database-based tools easily with the Google Gen AI Toolbox. It supports various databases, including Neo4j, PostgreSQL, MySQL, SQL Server, Spanner, and others. The toolbox provides a range of features to help applications hit production more quickly, such as end-user authentication in tools and built-in observability through OpenTelemetry. The Neo4j integration allows users to define sources and tools for Cypher execution, providing a flexible and powerful representation of connected information. This enables the creation of agentic LangChain applications with tools that use GraphRAG patterns combining full-text and graph search. The toolbox is open source, making it easy to contribute and reuse tools across different use cases. It provides a scalable and flexible solution for building AI agents with database-based tools.