A series on adopting the Model Context Protocol without creating a second, hidden application behind it — technical debt, shadow implementations, scaling, and OAuth, all solved by treating MCP as an interface to what you already run.

AI can generate an MCP server for any API in minutes — at 1,000 APIs, that's 1,000 implementations to own. Why the MCP Multiplication Tax is a bigger cost than tokens, and how to expose capabilities without reproducing them.

Why reaching for MCP elicitation usually means a tool's input contract has a gap; and how atomic, stateless APIs plus HAPI Workflows remove the need for it before it ever reaches the user.

Milano Software is using HAPI MCP to make reliable enterprise APIs accessible to AI without rebuilding its proven platform, across on-premise, air-gapped, hybrid, and cloud environments.

Turn a production OpenAPI spec into a live MCP server, preview its tools for context bloat, and generate a ready-to-use AI agent system prompt, one CLI, zero code, zero rewrites.

MCP is moving toward statelessness by spec. For HAPI MCP, that's not a new feature — it's validation of the architecture chosen from day one: MCP is a contract, not a server.

An MCP server that reimplements what your API already does becomes a shadow — code that looks right today and quietly drifts from the truth tomorrow. Here's how to keep MCP transparent instead.

Exploring why APIs will remain the stable foundation for software, even as MCP emerges as a new abstraction for AI agents.

Dear ,I hope this email finds you well and that you've been eagerly awaiting the latest update on K1s, our revolutionary project.I am excited to announce that the Alpha version of K1s is finally available! Check the documentation here. 📃It's been a...