Agentic AI instruction encoding. 86.8% vs JSON. Inference-free decode. Any channel.
Agentic AI mesh without the cloud. OSMP (Octid Semantic Mesh Protocol) is an open encoding standard for agentic AI instruction and computation exchange. It works across any channel — from a 51-byte LoRa radio packet to a high-throughput cloud inference pipeline — using the same grammar, the same dictionary, and the same decode logic. No cloud required. No inference at the decode layer. No central…
Inferred from the transports this listing declares (stdio). A client not listed here hasn’t been ruled out — it just isn’t something Forge can confirm.
Verification confirms publisher identity (repo ownership), not code safety. The security scan covers known CVEs and suspicious install scripts.
Forge read 0 source files from the published package tarball and matched no MCP tool registrations. Extraction is pattern-based over shipped source: a server that builds its tool list at runtime, or that ships only bundled or minified code, registers nothing this can see. Treat it as “not detected”, not as “exposes none”.
Agentic AI mesh without the cloud. OSMP (Octid Semantic Mesh Protocol) is an open encoding standard for agentic AI instruction and computation exchange. It works across any channel — from a 51-byte LoRa radio packet to a high-throughput cloud inference pipeline — using the same grammar, the same dictionary, and the same decode logic. No cloud required. No inference at the decode layer. No central authority. 35 bytes on the wire. Decoded by dictionary lookup, not inference. Fits a single LoRa…
Forge's dependency resolver reads npm metadata only, so this PyPI package has no resolved tree. That is a gap in coverage, not a clean bill of health.