As AI agents increasingly drive API traffic in ways that differ fundamentally from human usage patterns, traditional observability approaches fall short. Six concrete steps are outlined for API providers to gain meaningful visibility into agentic interactions: (1) maintain a definitive API catalog and MCP registry, (2) map how agents actually traverse workflows, (3) correlate API calls across agent sessions using agent ID tracing or workflow attestation, (4) use heuristics and traffic funneling to distinguish agent from human traffic, (5) log tool usage and intent at the MCP header level, and (6) set risk thresholds and anomaly triggers to surface escalated or sensitive requests for human review. The approach is framed as iterative, acknowledging the rapidly evolving agent landscape.
