RAG-Ready Patterns for Data Platforms

Chapter 8. Orchestrating RAG with the Model Context Protocol

Up to this point, we focused on getting the data platform “RAG-ready” by curating high-quality knowledge, exposing reliable metrics, and tightening governance. In this chapter, we focus on the next step: how to enable AI systems to use those capabilities on behalf of your users.

The Model Context Protocol (MCP) is an orchestration interface that makes this possible. MCP gives models a standard way to interact with tools, services, and data products on behalf of users—without baking platform-specific assumptions into prompts or bespoke code. Instead of hiding logic inside opaque agent frameworks, you expose your platform as a set of MCP tools and let models compose them into transparent, auditable retrieval and action chains in response to user intent.

This chapter introduces MCP as a universal connector for your data platform and then builds from basic tool exposure to human-governed workflows that were not previously practical to scale. In this chapter we will:

• Ground what MCP is and why it is seeing broad adoption.

• Map core data-platform capabilities—catalog, lineage, pipelines, cost, observability—into concrete MCP tool families.

• Walk through multi-step chains that remain explainable and interruptible, with explicit human-in-the-loop checkpoints.

• Outline an “agentification” playbook: how to evolve from raw tools to reusable, parameterized workflows.

• Show how MCP becomes the “central nervous system” of your ...