Data Product MCP: Chat with your Enterprise Data
Marco Tonnarelli, Filippo Scaramuzza, Simon Harrer, Linus W. Dietz

TL;DR
This paper presents Data Product MCP, a system that enables AI agents to discover, request, and query enterprise data products securely and efficiently, enforcing governance policies in real time within a data marketplace.
Contribution
It introduces the Model Context Protocol (MCP) integrated with a data marketplace to automate data access while maintaining governance standards.
Findings
Reduces technical burden for data analysis in enterprises.
Enforces data governance policies in real time during data queries.
Received positive feedback from 16 data governance experts.
Abstract
Computational data governance aims to make the enforcement of governance policies and legal obligations more efficient and reliable. Recent advances in natural language processing and agentic AI offer ways to improve how organizations share and use data. But many barriers remain. Today's tools require technical skills and multiple roles to discover, request, and query data. Automating data access using enterprise AI agents is limited by the means to discover and autonomously access distributed data. Current solutions either compromise governance or break agentic workflows through manual approvals. To close this gap, we introduce Data Product MCP integrated in a data product marketplace. This data marketplace, already in use at large enterprises, enables AI agents to find, request, and query enterprise data products while enforcing data contracts in real time without lowering governance…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
