MCP Toolbox for Databases: Connecting AI Agents to Enterprise Data
Detaylar
As generative AI moves beyond chat interfaces into autonomous, production-ready workflows, one major challenge remains: how can AI agents securely and efficiently interact with enterprise databases?
In this session, Stenal P. Jolly, Senior Cloud Architect at Google Cloud, and Anubhav Dhawan, Software Engineer at Google, will introduce MCP Toolbox for Databases—an open-source, enterprise-grade server built around the Model Context Protocol (MCP).
You’ll learn how MCP Toolbox enables AI agents, developer tools, and production applications to securely access structured enterprise data without requiring teams to build and maintain custom integration code for every database or application.
The session will explore support for 30+ database engines, including:
- Google Cloud databases such as AlloyDB, BigQuery, and Spanner
- PostgreSQL
- MySQL
- Oracle
- MongoDB
- and many more.
Through practical examples and demonstrations, Stenal and Anubhav will show how developers can connect AI-powered applications and agents to enterprise databases while maintaining security, scalability, and performance.
### About the Speakers
Stenal P. Jolly is a Senior Cloud Architect at Google Cloud with nearly a decade of experience in software engineering, cloud architecture, microservices, and distributed systems. Before joining Google in 2021, he worked at organisations including Zoho Corporation, Cisco, and Synamedia, where he developed cloud-connected and edge computing solutions for major global clients. He also co-founded Semantica during his engineering studies.
Anubhav Dhawan is a Software Engineer at Google and will join Stenal to share technical insights and practical demonstrations around MCP Toolbox for Databases, AI agents, and enterprise data. View Anubhav Dhawan on LinkedIn
This session is ideal for data engineers, software developers, cloud architects, AI/ML practitioners, and anyone interested in building production-ready AI agents that interact with enterprise data.