Ignoring for a moment all of the other functions that MCP can allow an agent to do (open a webpage, query a database, run another agent, execute local commands etc) and only focussing on the use of MCP to provide context, the big advantage of MCP over RAG is that a RAG system needs to be built and maintained: you need to extract your content, vectorise it, store it in a database, query it, update it etc etc. With MCP, you just point it at your database and the agent gets up-to-date info.
Those things are not mutually exclusive. We use RAG and Vector stores to index terabyte of data.
Then use tools calls (MCP) to allow the AI to write SQL to directly query the data (vector store).
I think in that case, you would still need RAG - I can't imagine someone is going to build an MCP server to a folder of docs and even if they did, it would still need to index them, extract data etc. BUT if you were feeding your Confluence pages into RAG, then that's probably not worth doing anymore (because there is an MCP server for that).
In short, MCP servers won't make RAG obsolete, but the number of use cases is definitely lower than it was without it.
Isn't that indexing part of RAG? I've been always read about RAG as a two step process, creating and maintaining the vector database, and then using that database to feed the AI.
