AI application
App-defined
StructureValidationChangeAuditGovernance
A protocol for persistent AI memory.
MOPS is a vendor-neutral protocol for persistent AI memory. It defines shared, deterministic rules for how memory is identified, structured, changed, verified and governed across agents, models, devices and storage systems.
MOPS 1.0-rc4Public Review
02The problem
Persistent AI memory has no common protocol.
Every system has to build its own.
Applications, agent frameworks, device environments and vendor ecosystems therefore define their own memory structures and rules.
Each implementation can decide for itself how memory is represented, validated, changed, versioned, audited, retained and governed.
Those decisions do not have to agree.
Memory can work inside one system and still become difficult to preserve, verify or move when models change, agents collaborate, devices change, storage changes or users move between vendors.
Diagram — Divergence
No common persistent-memory protocolindependent implementations
Agent framework
Framework-defined
StructureValidationChangeAuditGovernance
Device environment
Device-defined
StructureValidationChangeAuditGovernance
Vendor ecosystem
Provider-defined
StructureValidationChangeAuditGovernance
Independent definitionsDifferent memory semantics
Without shared rules, the same underlying information can acquire different structures, transition behaviour, histories and governance.
The result is fragmented memory semantics and a growing layer of custom integration between otherwise capable systems.
03The common protocol
A common protocol for persistent AI memory.
MOPS standardises the persistent-memory rules that systems currently have to define independently.
It defines how persistent memory is identified, structured, validated, changed, committed, verified, audited and governed.
Applications, agents, models, devices and storage systems can continue to evolve independently. MOPS defines the memory semantics that need to remain stable across those changes.
This creates a shared foundation for long-lived AI memory without prescribing the model, application architecture or physical storage implementation.
Diagram — Shared protocol layer
Modelsvia Agents
ApplicationsAgentsDevice runtimes
Shared M-OP Requests
MOPS
Common persistent-memory protocol
Shared deterministic rules
identityschemastateoperationstransitionslineagepolicyconformance
Backing-store adapter boundary
Local storeDatabaseDistributed storage
A stable foundation for long-lived AI memory.
Systems and infrastructure can evolve independently while persistent-memory semantics remain explicit and verifiable.
04What a common memory protocol enables
A shared foundation for AI memory to grow on.
Standardise the persistent-memory foundation so everything around it can continue to evolve.
MOPS gives persistent memory common semantics without prescribing the models, applications, agents, devices or storage systems that build on them.
Memory that survives change
Models can be upgraded, applications rebuilt, devices replaced and storage changed without requiring persistent memory to lose its identity, meaning or history.
Namespace · Schema Version · State · Lineage
Systems that understand the same memory
Explicit structures and deterministic rules give independent implementations a shared way to interpret, validate and operate on persistent memory.
Schema · State · M-OP · Conformance
Safe evolution
Memory structures can evolve through explicit versions and migrations while preserving what earlier State meant and how it was produced.
Schema Version · Migration · State · Audit Trail
Multiple agents working from the same foundation
Agents can act on shared persistent memory using common identity, operation and transition semantics instead of maintaining incompatible private interpretations.
Namespace · M-OP · State · Commit Record
Memory that can be inspected and governed
Accepted changes preserve verifiable lineage, while common policy semantics define access, retention, expiry, deletion and redaction behaviour.
Commit Record · Audit Trail · Policy
Innovate with confidence
Applications, models, agents, devices and storage technologies can develop independently with confidence because the persistent-memory semantics they rely on remain explicit and testable.
Conformance · Extensions · Custom Schemas
By replacing fragmented memory semantics with a shared foundation, MOPS allows the AI ecosystem to evolve independently without continually reinterpreting or reinventing persistent memory.