MCP

As AI agents move from demo toys to production infrastructure, the question of how they connect to backend services has become a serious architectural decision. There are currently two dominant strategies: exposing capabilities through REST APIs paired with structured skill documents, and exposing capabilities through MCP (Model Context Protocol) servers. The popular framing — that REST is legacy and MCP is the future — oversimplifies the tradeoff. REST APIs, particularly when backed by machine-readable specifications like OpenAPI, offer strong contracts, broad compatibility, and mature tooling. MCP offers agent-native tool discovery, session-aware invocation, and push-based capability updates designed specifically for LLM tool use. Neither subsumes the other. This essay examines the two strategies across three dimensions — contract strength, orchestration control, and adaptability to code changes — and argues that the right choice depends on who your consumers are, what granularity they need, and how much backend volatility you expect them to absorb. ...