In a previous episode, I ran quite a few tests and experiments to understand how to code for an MO5. I had asked the AI to summarize what we had learned into Markdown files. The underlying idea was to be able to share this experience with my new MO5 projects without having to copy .md files into each repository. Spoiler alert: vibe coding costs money 😢 The RAG server idea One simple way to share knowledge and context is through a RAG server. ...
In the previous episodes, I talked about my RAG server, why it exists and how it helps me provide context to AIs. But as my experiments progressed, I realized an important point: a RAG server, no matter how well built it is, is not sufficient for a smooth and robust integration with modern AIs. There is a missing building block to connect coding agents to my RAG server. In this article, I will explain: ...
Following the previous episode (/mo5-blog/days/day-6-rag-server/), I wanted to go one step further: deploy my RAG server on the Internet. The goal was twofold: make the server accessible from the outside allow coding agents (Copilot, Augment, etc.) to have a precise context to help with MO5 development (the project is described here: https://retrocomputing-ai.cloud/) Deploying a RAG, but not just an API To connect coding agents with my RAG server, I created an MCP server. It acts as a standardized interface between AI tools (Copilot, Augment, etc.) and my RAG API. ...