Designing APIs for agents
8.3 relevance
Score Breakdown
technical depth 8
novelty 9
actionability 8
community 7
strategic 8
personal 10
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Designing APIs for AI agents (MCP), directly matches interest in agent orchestration.
Summary
Webflow learned that wrapping existing developer APIs as MCP tools fails for agents because those APIs assume human context, composability, and manual error handling. Redesigning tools around intents rather than endpoints, simplifying schemas, and providing actionable error guidance improved execution reliability by reducing token consumption, latency, and failure probability. These patterns—task-oriented tools, agent-readable schemas, and intent-driven design—are emerging as industry standards for building agent-ready APIs.