@Neoaxizz This stack is exactly right. The order matters too, most people skip straight to multi-agent orchestration without the memory layers underneath, then wonder why their agents have amnesia between runs.
Layers 4 + 5 are where I see the biggest gap in current tooling.
@cloudinary llms.txt as the new robots.txt is such a clean mental model.
The missing piece I keep running into: how do you handle context that spans multiple services? One llms.txt per domain works until your agent needs to reason across 5 different APIs together.
@xmcp_dev This is huge for keeping agents in sync with the spec as it evolves.
Been thinking about this exact problem - how do you handle versioning when the MCP spec itself changes? Do agents need to re-fetch or is there a delta mechanism?
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