caura
Multi-agent systems require secure, auditable memory isolation to prevent data leakage and ensure compliance.
Caura (formerly MemClaw) — 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.
- Ask Claude to audit which agents accessed sensitive data across your multi-tenant deployment yesterday.
- Generate compliance reports showing memory access patterns and policy violations for regulatory reviews.
- Automate knowledge sharing between AI agents while enforcing role-based access control rules.
Multi-agent systems require secure, auditable memory isolation to prevent data leakage and ensure compliance. Caura's trust-tier architecture and keystone policies reduce breach surface while maintaining operational efficiency across tenant boundaries.
Enterprise AI platforms deploying multi-tenant agent fleets with strict data governance and audit requirements.
https://github.com/caura-ai/caura
By caura-ai
How to Get It
claude plugins install caura-ai/caura
Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.
Auto-generated from the tool's public listing — not hands-on verified. Cross-check against the source repo's README before running.
After installing, paste this into Claude:
Audit which agents accessed sensitive data across my multi-tenant deployment yesterday
Trust Signals Auto-scanned
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
Scored from trust signals (evidence-eval-v1): 468 GitHub stars; contributors unknown; last commit 0d ago; license Apache-2.0.
Things to check
- Scanned, not hands-on tested — this entry was auto-scanned from public metadata (GitHub metrics, license, security flags). No reviewer has run it, and no tool-specific limitations have been documented yet.
How to evaluate tools before deploying →
Data shown here comes from public APIs and automated scanning. Reviewer notes reflect one person's experience. This is not a security certification or legal recommendation. Always evaluate tools according to your own organization's policies.
Evaluation
Scored from trust signals (evidence-eval-v1): 468 GitHub stars; contributors unknown; last commit 0d ago; license Apache-2.0.