Open Memory Protocol Initiative
Open-source ecosystem developing the Open Memory Protocol — an open technology for portable, interoperable AI-agent memory. Hosted at the AI Disclosures Project (Code for Science & Society).
A multi-stakeholder ecosystem for portable AI memory
OMPI incubates open, interoperable specifications for portable AI memory. It is housed at the AI Disclosures Project, a project of Code for Science & Society, and runs as a light-weight working group with in-person convenings and monthly digital meetings.
The goal is decentralized, competitive AI markets with specialized producers and modular technological pieces.
Specifications are model-, harness-, and application-agnostic. Multi-user memory, provenance, and privacy are first-order design considerations. In AI systems, memory is part of the context layer that enables personalization and agentic action — user-provided or model-learned, scoped to a project, user, or organization.
Artifacts and specs
Specs
Letta Draft Spec v0.2
Expanded schema, provenance, and lifecycle. Charles Packer (Letta).
Read draftAI Disclosures Project Draft Spec v0.1
Draft OMP spec from the AI Disclosures Project. Sruly Rosenblat.
Read draftme.md
User-owned plain files. Agents propose; users decide. David Hamilton (Block / goose).
View on GitHubOther
State of Agent Memory
Survey of memory implementations across coding, consumer, and enterprise systems (Aug 2026).
Read noteGovernance Model
Technical Steering Group, consensus decisions, royalty-free licensing, Month-24 review.
Read governanceMemory is becoming a core agent layer without shared exchange semantics
Agent memory is persistent context that shapes future model or agent behavior — user facts, derived summaries, project instructions, prior decisions and actions.
Every major coding-agent harness (Claude Code, Codex, goose, OpenClaw, Letta Code) implements memory with a different convention. Developers cannot move a stateful agent across harnesses. Enterprises cannot switch memory providers without re-ingesting derived objects. Open-source memory projects duplicate one another for lack of a shared object model.
Fragmentation has engineering and security costs: bespoke adapters, lost provenance on copy, permissions that don't survive export, harder security review. A common open layer addresses this without dictating how each agent reasons, summarizes, indexes, or retrieves.
Partners and implementers
Mozilla
Co-hosts convenings, leads ecosystem recruitment across Mozilla's open-source and AI-developer network.
IBM
Co-hosts convenings, contributes enterprise-adoption pathways, advises on standards-body process.
Letta
Contributes MemGPT / Letta memory-object model and the open-source Trajectory package.
Block / goose
Open-source agent harness on the Model Context Protocol. First-vertical implementation target.
From ecosystem launch to sustainable stewardship
Join the ecosystem
If you build agent memory, maintain a coding-agent harness, run a memory-layer service, or contribute to open AI infrastructure, join OMP. Our Discord is a working-group space for implementer Q&A and convening coordination — membership is by application.
Email OMPI Discord GitHub

