memorywire: A Vendor-Neutral Wire Format for Agent Memory Operations
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Abstract (arXiv)
Agent-memory frameworks -- mem0, Letta/MemGPT, Cognee, Zep/Graphiti, MemoryOS, MemTensor -- each ship their own SDK, storage layout, and operational vocabulary. There is no shared wire format: every integration is bespoke, every migration rebuilds memory from scratch, and no framework ships a governance surface that lets a human review writes before they enter long-term storage. We present memorywire, a JSON-Schema 2020-12 wire format for five memory operations (remember, recall, forget, merge, expire) over four memory types (semantic, episodic, procedural, emotional), with a MemoryStore interface, a fan-out router, and an optional HITL governance channel. We describe an open-source reference implementation with five backend adapters (sqlite-vec, mem0, Letta, Cognee, pgvector); a microbenchmark on a 100-fact / 50-query labelled corpus (42 with non-empty gold ids + 8 no-match probes) achieving recall@5 = 1.000 on the 42 gold-id queries with ingest p50 = 37.8 ms and recall p50 = 40.6 ms; an adversarial-fusion experiment showing Reciprocal Rank Fusion holds recall@5 = 1.000 across a 1-of-N rank-0 injection sweep (K in {0, 5, ..., 50}) where max fusion collapses to 0.500 with 80% leak at K >= 5; and a 16-scenario cross-adapter conformance suite passing 68 of 80 cells with zero failures. The contribution is not a new algorithm; it is a packaging of established components (RRF, FSMs, STM/LTM consolidation, diff-and-approve workflows) into a venue-neutral protocol with an empirically validated reference, positioned to compose with the Model Context Protocol rather than compete with it. We further show that memorywire's provenance field is the strongest lever for recovering a poisoned store, evaluated with an companion benchmark (PurgeBench).
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 4 of its 12 references that are in the map. First posted on arXiv 31 May 2026.
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4 of 12 references.
References · 4
- 2024Evaluating Very Long-Term Conversational Memory of LLM Agentscited by 830
- 2025Mem0: Building Production-Ready AI Agents with Scalable Long-Term Memorycited by 779
- 2024LongMemEval: Benchmarking Chat Assistants on Long-Term Interactive Memorycited by 707
- 2026Governed Memory: A Production Architecture for Multi-Agent Workflowscited by 6
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Citing papers per year: 2026: 2.
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- 2026Are We Ready For An Agent-Native Memory System?
- 2026Storage Is Not Memory: A Retrieval-Centered Architecture for Agent Recall