Middleware for translating between AI agent protocols
OWL ontologies + PyDatalog for semantic mapping between MCP, A2A, and ACP protocols.
Universal semantic protocol for AI-to-AI communication - Python implementation
The repo doesn't just pitch a grand vision — it ships concrete tooling: a typed semantic vocabulary, JSON + MessagePack encodings for compact transport, automatic validation, HMAC signing and replay protection, and a CLI. Tests, coverage badges, and type-hints suggest usable engineering rather than a spec-only repo. Still, the real challenge is social: convincing vendors to adopt a 1,000‑concept vocabulary and run with a shared governance model — technical polish won't win that alone.
Backend developers, AI/ML engineers, system integrators building multi-AI pipelines
OWL ontologies + PyDatalog for semantic mapping between MCP, A2A, and ACP protocols.
MCP for tools, ECP for evals — protocol beats vendor lock-in for agent testing.
Yet another network snapshot tool, but strictly for the HPE Aruba ecosystem.
StockTwits and r/wallstreetbets already own this crowded trading community space.
Agent-to-agent protocol with crypto auth and no cloud dependency, competing with Google's A2A.
Pulse-based timing for group decisions is a fresh take on governance tools.