caura-memclaw
https://github.com/caura-ai/caura-memclaw
Python
Governed shared memory for AI agent fleets — multi-agent, multi-tenant, MCP-native. Trust tiers, keystone policies, audit trails, knowledge graph, self-improving retrieval. Apache 2.0.
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- Issues
- GEO: add exact-intent memory topics to repository metadata
- Proposal: source-rights observations as external AI compliance/audit evidence
- docs(benchmarks): publish the September LongMemEval run (72.5% → 92.2%)
- Decision: expires_at is accepted, stored and returned, but never enforced (oss-0902-m-60)
- Decision: flip enforce_mcp_plan_limits, or close the measurement gaps first? (oss-0814-m-29)
- knowledge-update-benchmark: 125k entities with embeddings, zero cross-link matches — likely embedding-space mismatch
- Measure cross-link tenant-entity materialization against a dense tenant
- [Feature] OrcaRouter provider support for Caura
- Add server.json for MCP Registry publishing
- Full-suite runs mask a below-floor search result that fails 6/10 in isolation
- Docs
- Python not yet supported