MemClaw vs. Letta

Letta (formerly MemGPT) pioneered stateful, self-editing memory for an individual agent. MemClaw targets the layer above the single agent: governed memory shared across a fleet — multiple agents, teams, and vendors on one auditable plane, with an auto-extracted knowledge graph and contradiction handling built in.

CapabilityMemClawLetta
Multi-fleet support
Agent trust tiers + keystone policies
Cross-vendor memory sharing
Contradiction detection + supersession
Per-agent retrieval tuning
PII detection & quarantine
Audit trail / provenance
Knowledge graph (auto-extracted)
MCP-nativePartial
OSS licenseApache 2.0Apache 2.0

Where MemClaw differs

  • Fleet-scoped shared memory. Memory is shared and governed across many agents and tenants, rather than living inside one agent’s state.
  • Auto-extracted knowledge graph. Entities and relations are extracted on write and used to expand recall through graph hops.
  • Governance & provenance. Trust tiers, keystone policies, contradiction detection with supersession, and audit trails on every operation.
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Comparison reflects our reading of each project’s public documentation as of June 2026. Mem0, Zep, and Letta are solid projects for single-agent memory. Spot something out of date? Open an issue or PR and we’ll correct it.