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Show HN: Middleware for translating between AI agent protocols

https://github.com/kwstx/engram_translator
1•kwstx•1h ago
I’ve been working on a problem that kept coming up while building multi-agent systems: agents don’t interoperate cleanly.

Even when two agents can technically connect, they often: - use different schemas - structure intent differently - break when assumptions don’t match

So you end up writing a lot of brittle glue code just to pass messages around.

I built a middleware layer to sit between agents and handle this:

- schema-aware translation between protocols - semantic mapping (so intent stays consistent across formats) - orchestration of agent-to-agent handoffs

The goal is to let agents communicate without forcing everything into a single standard or rewriting existing systems.

One thing I’m still figuring out is how far abstraction should go — at some point, “translation” can hide important differences instead of resolving them.

Curious how others are thinking about this: - Are you standardizing on one protocol? - Building internal adapters? - Or avoiding cross-agent interoperability altogether?

Would really appreciate any thoughts or criticism.

Project: https://www.useengram.com/

Comments

kwstx•1h ago
A bit more context on how this works under the hood:

Right now the middleware sits as a translation/orchestration layer between agents. Instead of forcing a shared schema, it:

validates payloads at the boundary maps fields across schemas (configurable mappings) preserves intent via a semantic layer (still evolving)

One thing that surprised me is how often agents “technically integrate” but still fail at the intent level especially when message structures look similar but mean slightly different things.

Still early, but I'm trying to figure out: how much of this should be automatic vs explicitly defined whether a “universal intermediate schema” is actually a bad idea how people handle versioning across agent protocols

Happy to share more details if useful.

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