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Enforce compliant AI-to-data access with masking, policy controls, and audit trails.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "Aegis" yet — see the docs or source repo.
Design a compliance access layer for my MCP setup: AI agents need to query a customer database, but field access must be role-based, phone numbers and national IDs must be masked, and full audit logs must be recorded. Provide policy rules, access flow, and sample configuration.
A compliance design including access controls, sensitive data masking, audit logging, and sample configuration.
I have multiple AI agents for support, analytics, and operations. Help me define data access policies: support can only view limited customer fields, analytics can access only aggregated data, and operations cannot read any PII. Output a clear policy matrix and enforcement rules.
A role-based data permission matrix and enforceable policy rule definitions.
Help me design an MCP-focused audit plan to track what data AI agents accessed, which policies were triggered, which requests were denied, and how to generate compliance audit reports. Include recommended log fields.
A complete audit design covering access logs, policy hits, denied events, and audit report structure.
Keep AI coding agents architecture-aware, verified, drift-checked, and safer over long tasks.
Add cited compliance checks and standards mapping to AI assistants.
Monitor, policy-check, and audit every AI agent tool call.
Audit MCP servers and AI packages for security and supply chain risks.
Audit MCP configs for exposed access, secrets, models, and compliance AI-BOMs.
Scores AI agents for trust, permissions, and silent-failure risk.