Open specifications for AI agent memory, architecture, and identity.
No databases. No embeddings. No cloud services. Just files.
Five protocol specifications that define how AI agents can persist memory, maintain architecture awareness, discover identity, and manage session lifecycles — all without external databases.
These protocols were invented while building Soma, an AI coding agent with self-growing memory. They're published here as standalone specifications that any agent framework can implement.
| Protocol | Spec | Description |
|---|---|---|
| AMP | v0.1 | Agent Memory Protocol — filesystem-based persistent memory with muscles, preloads, heat tracking, and promotion |
| ATLAS | v0.1 | Architecture Truth Layered Across Stacks — living system maps with frontmatter standards and hierarchy |
| Breath Cycle | v0.1 | Session lifecycle — inhale (boot) → process (work) → exhale (flush) → rest. Context depletion as design |
| Three-Layer Model | v0.1 | Extensibility — Extensions (code) + Skills (knowledge) + Rituals (workflows) |
| Identity System | v0.1 | Contextual identity — agents discover who they are based on where they are |
| Git Identity | v0.1 | Multi-repo attribution — path-based author resolution, agent vs human commits |
┌─────────────────────────────────────────────┐
│ Identity System → who am I here? │
│ Breath Cycle → session lifecycle │
│ AMP → what do I remember? │
│ ATLAS → what does this system │
│ look like? │
│ Three-Layer Model → how am I extended? │
└─────────────────────────────────────────────┘
An agent boots, discovers its identity, inhales (loads preload + muscles via AMP), reads the ATLAS state, works with its three-layer capabilities, then exhales (writes preload) when context fills up. The cycle repeats.
Most frameworks treat agent memory as a retrieval problem — vector databases, embeddings, RAG pipelines.
These protocols take a different approach: the agent reads and writes plain files. Like a human with a notebook.
This works because:
- LLMs are excellent at reading and following written instructions
- Filesystem operations are universal — any language, any OS, any framework
- No infrastructure required
- The agent can inspect and curate its own memory
- Humans can read and edit it too (it's just Markdown)
These specs are in draft v0.1. They describe systems that are implemented and working in Soma, but the spec documents are still being formalized.
Feedback, questions, and implementation reports welcome — open an issue.
You're free to implement these protocols in your own agent framework. Licensed under CC BY 4.0 — use them however you want, just credit the source.
This project implements the Agent Memory Protocol (AMP)
by Curtis Mercier (https://github.com/curtismercier/protocols)
Soma is the reference implementation. MIT-licensed, open source.
- GitHub: github.com/meetsoma
- Website: soma.gravicity.ai
CC BY 4.0 — see LICENSE.
Moral rights asserted under the Canadian Copyright Act.
By Curtis Mercier · Gravicity