MCP vs. Agentic RAG: A Guide to Enterprise AI Architecture Choices
femke_plantinga · x · 2026-08-05
When building AI applications for enterprise teams, MCP (Model Context Protocol) and Agentic RAG are two widely discussed architectures. The author compares their mechanics using the exact same prompt ("What onboarding feedback do we have in Intercom and Slack?"):
- MCP (Direct & Structured): MCP is a standardized protocol acting as a USB-C for AI. The client connects to a server, discovers tools on the fly, and fetches data across Slack, Intercom, etc. With human-in-the-loop approval, data flows directly to the model. The shape is tool connected → data retrieved → answer—fast, structured, and typically one hop.
- Agentic RAG (Reasoning & Looping): It is a reasoning loop wrapped around retrieval that actually "thinks" rather than just fetching. It checks memory first (have we answered this before?) and breaks down complex questions.
- Takeaway: The author notes a major trap in building enterprise AI in 2026 is thinking you have to pick just one, whereas a hybrid approach leveraging both is often optimal.
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