AWS and Cisco AI Defense secure AI agents with automated MCP and A2A scanning
New AI Registry and Cisco integration tackle visibility, security, and compliance gaps at scale
Enterprises face three critical security gaps as they scale AI agents using Model Context Protocol (MCP) and Agent-to-Agent (A2A) protocols: lack of visibility into deployed tools, manual security reviews that can’t keep pace, and missing audit trails for autonomous agents. Without centralized governance, teams risk exposing sensitive data, violating SOX/GDPR frameworks, and suffering operational disruptions from unvetted servers or malicious agents. Manual reviews add weeks to each deployment, creating backlogs and regulatory exposure.
To address this, the AWS-backed AI Registry (open-source) integrates with Cisco AI Defense to offer unified registration and automated scanning. Every MCP server, A2A agent, and Agent Skill is registered in a single control plane. When a new component is added, Cisco AI Defense automatically analyzes it for vulnerabilities, malicious code, or insecure patterns. If issues are found, the component is marked disabled with a security-pending tag for administrator review. This transforms slow manual processes into automated, self-service onboarding with built-in security guardrails, enabling enterprises to scale AI agent deployments securely and comply with regulations.
- AI Registry provides unified visibility by registering every MCP server, A2A agent, and Agent Skill in a single control plane.
- Cisco AI Defense auto-scans registered components for vulnerabilities, marking them disabled if issues are found.
- Automated scanning reduces manual review from weeks to minutes, accelerating deployment while ensuring compliance.
Why It Matters
Automated AI agent security at scale enables faster, compliant enterprise AI adoption without manual bottlenecks.