REST APIs, MCP servers and agents: how the layers connect in production.
AI Agents autonomously orchestrate tools and make decisions. Part 3 completes the picture with agent code examples, full comparison tables, common misconceptions, and real-world architectures showing how REST APIs, MCP servers, and AI agents work together in production systems.
MCP Servers bridge traditional APIs and AI agents. Part 2 covers the Model Context Protocol—resources, tools, prompts—with full code showing how to convert a REST API into an MCP server. Explains capability negotiation, stateful connections, and when to use MCP.
Developers confuse REST APIs, MCP Servers, and AI Agents. Part 1 explores REST APIs—what they are, how they work, and why they're suboptimal for AI systems. Includes practical code examples and explains the foundation for modern AI architectures.
