WebMEM™ Protocol
The Protocol for Structuring, Delivering, and Conditioning Trust-Scored AI Memory.
Build agent-ready content. Publish with memory. Align your data with the future of AI trust and retrieval.
What Is WebMEM?
WebMEM™ is a universal protocol for encoding structured, retrievable memory into web content. It enables AI systems and agentic frameworks to retrieve, trust, and reflect on public data using embedded fragments, glossary-scoped definitions, and provenance-based scoring. Designed for compatibility with MCP, A2A, and memory-first publishing architectures.
Core Components
- SDT – Semantic Data Templates: YAML and Python memory fragments embedded in inert HTML for declarative and procedural recall.
- SDP – Semantic Digest Protocol: A structured delivery layer for surfacing, exporting, and reflecting memory fragments.
- GTP – Glossary Term Protocol: Ontology-linked definitions with trust layers, correction logic, and co-citation indexing.
- Semantic Reflection Method: A feedback loop protocol for conditioning AI model behavior via structured memory interactions.