MCP Servers Are APIs — Monitor Them Like APIs

Your AI agent discovers tools via MCP. Those tools change. Your agent doesn't crash — it confidently returns wrong results. If that sounds familiar, it's the same problem REST APIs have had for years. But MCP makes it worse. The discovery flow that breaks silently Here's how MCP works in practice: Agent connects to an MCP server Agent calls tools/list to discover available tools Agent reads tool schemas — names, parameters, return types Agent calls tools as needed This works beautifully... until the MCP server updates. Tools get renamed. Parameters become required. Return schemas evolve. The server doesn't version these changes. There's no changelog. There's no deprecation header. Your agent's cached understanding of the tool catalog goes stale. Why MCP drift is worse than REST drift When a REST API changes, your code usually fails loudly: TypeError: Cannot read property 'tracking_number' of undefined HTTP 400: Missing required parameter 'format' Noisy failures. You notice them. You de