MCP is production infrastructure, not a prototype shortcut. Unlike enterprise APIs designed for deterministic software callers, MCP serves autonomous AI agents, which demands different interface design principles: high-intent single-call interfaces instead of nested resource hierarchies, structured error responses that enable agent self-correction, and scoped OAuth 2.0 tokens per agent session for fine-grained auth and audit trails. Response sanitization matters because verbose outputs increase LLM hallucination risk. Latency SLOs from enterprise APIs should carry over, but logging must capture session-level reasoning chains rather than isolated requests. Capacity planning is harder because agent-driven traffic is bursty and unpredictable — fan-out from a single prompt can spike load instantly — so load testing should simulate abrupt surges rather than gradual ramp-ups.

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Your inbox, upgraded.Fundamental interface differences between API and MCPSecurity and authenticationMore like thisLatency and loggingScalability and capacity planningMCP in the era of APIs and AI agents

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