# What's the difference between MCP and RAG?

RAG pulls outside material into the model's context before it answers; MCP lets an agent discover and call a tool. A retriever can be that tool. The retrieval pipeline can be [fully managed](https://docs.aws.amazon.com/prescriptive-guidance/latest/retrieval-augmented-generation-options/rag-fully-managed-bedrock.html), and the [MCP server can be one you run yourself](https://ts.sdk.modelcontextprotocol.io/v2/get-started/first-server), so neither term tells you whose deployment it is.

A stale retrieved chunk can make the answer wrong whether the agent reached the retriever through MCP or not. A changed MCP tool schema can stop the call before retrieval even starts. [Whether retrieval runs automatically or gets called as a tool](/answers/tool-calling/whats-the-difference-between-tool-calling-and-rag) is separate from both.

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Sources:
- Amazon Bedrock: Knowledge bases for fully managed RAG: https://docs.aws.amazon.com/prescriptive-guidance/latest/retrieval-augmented-generation-options/rag-fully-managed-bedrock.html (fetched 2026-09-25)
- Model Context Protocol TypeScript SDK: Build your first server: https://ts.sdk.modelcontextprotocol.io/v2/get-started/first-server (fetched 2026-09-25)

Source: https://tessary.ai/answers/mcp-tool-reliability/whats-the-difference-between-mcp-and-rag
More on Mcp tool reliability: https://tessary.ai/answers/mcp-tool-reliability
From Tessary, agent reliability for AI agents in production: https://tessary.ai