# MCP vs RAG: how should AI agents get context?

> RAG finds text similar to a query; MCP is the interface an agent uses to ask a source for context. They solve different problems, and neither one decides which source is authoritative for a fact. That job belongs to a governed context layer behind MCP, with retrieval running inside it.

_Comparisons · 2026-07-06_

**Short answer: RAG is *how you find* relevant text; MCP is *how an agent talks to* a context source. They are not competitors; the strongest setups use both.** Confusing them leads to agents that retrieve plausible snippets but still act on stale or contradictory information.

## RAG finds similar passages and cannot tell you which source wins

RAG has no concept of **authority**, **freshness across tools** (the ticket changed after the doc was written), or **contradiction** (two sources disagree).

Retrieval-Augmented Generation embeds a corpus, finds passages similar to a query, and stuffs them into the prompt. For a single, mostly-static knowledge base, that is often all you need.

## MCP standardizes how an agent asks for context and leaves the answer to you

Serving RAG results over MCP upgrades the interface and leaves the answer exactly as good as it was. The protocol defines the pipe; you still choose what flows through it. Read the specification and the gap is explicit: [at revision 2025-11-25 the MCP Resource type declares nine fields and none of them records which source is authoritative](/en/blog/insights/is-mcp-enough-for-shared-context).

The Model Context Protocol is an open interface an agent uses to ask for context and to write observations back. It standardizes the *conversation* between an agent and a context source, regardless of what is behind it.

## The strongest setup runs retrieval inside a governed context layer and serves it over MCP

A **governed context layer** behind MCP is what turns a retrieved passage from an answer into a candidate.

| Concern | RAG alone | MCP + context layer |
| --- | --- | --- |
| Find relevant text | ✅ | ✅ |
| Resolve duplicate identities | ❌ | ✅ |
| Authority per fact (which source wins) | ❌ | ✅ |
| Withhold contested facts | ❌ | ✅ |
| Agents write back | ❌ | ✅ |

The agent asks over MCP, retrieval surfaces candidates, and the governance layer decides what is trustworthy enough to serve. [See how LoomSignal structures this](/en/docs/architecture).

## Choosing MCP over RAG is choosing an interface over a search technique

Don't pick MCP *or* RAG. Use RAG as one signal, MCP as the interface, and a governed context layer to make the answer something an agent can safely act on.

---
Source: https://loomsignal.io/en/blog/comparisons/mcp-vs-rag-for-agent-context