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MCP and the Challenge of Feeding Governed Data to AI

Your Agents are Hungry for Context

About this Research Note

Your Agents are Hungry for Context: MCP and the Challenge of Feeding Governed Data to AI

Region: Global
Authors: Kevin Petrie and Florian Bigelmaier

The Model Context Protocol (MCP) standardizes data connectivity, reducing friction when integrating data sources and AI applications to accelerate agent development. However, MCP alone will not be enough to supply agents with data in a safe and governed manner. To deliver accurate results, they must be grounded in business reality based on a trustworthy data foundation. This report shows that successful enterprise agents require a combination of:

  • Model Context Protocol (MCP) for source connectivity and data access.
  • Retrieval-Augmented Generation (RAG) for retrieving domain-specific information.
  • A Semantic Layer to make sense of the retrieved data.
  • Governance controls to reduce various risks.

By integrating these elements, enterprises can develop and optimize advanced agents more rapidly. This report details the strengths, but also the shortcomings, of MCP and the role it can play in your agent infrastructure.

Readers of this report will learn:

  • How MCP reduces friction while connecting agents with data sources.
  • Why MCP is not enough for “grounding” agents.
  • How RAG, a semantic layer and governance aspects complement MCP.
  • Steps to implement this four-part strategy for grounding agents in trustworthy data.

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