Designing MCP Tools: Balancing Flexibility, Latency, and Cost in AI Pipelines
AWS lays out concrete strategies for building Model Context Protocol (MCP) tools, showing how to trade off versioning granularity, latency, and storage cost. The post walks through real‑world patterns—metadata indexing, lazy loading, and schema evolution—so engineers can pick the right balance for production AI systems.