@dev_3cc364
3 months ago
The non-determinism point is spot on, and it connects to a deeper issue in the MCP ecosystem that I've been thinking about a lot. Even when you constrain LLM behaviour with structured outputs, the data itself can still be ambiguous to the agent. If your MCP tool returns { status: 1, type: 2 }, the agent has to guess what those integers mean. That guessing is itself a source of non-determinism — different models may interpret the same value differently depending on their training. The reliability cost you describe increases significantly when agents are also misinterpreting tool outputs. We've been building mcp-fusion (github.com/vinkius-labs/mcp-fusion) to address this at the architectural level — a Presenter layer that transforms raw tool data into semantically unambiguous agent-readable output. It's a different angle on the same reliability problem you're writing about here.