What Building with MCP Taught Me About Its Biggest Gap

I spent the last few weeks wiring up MCP at my org, stitching a handful of internal tools (GitHub, Slack, Datadog) into a shared layer that multiple teams' AI agents could call into. Useful. Powerful. And, about a week in, slightly alarming. The same four or five "wait, doesn't MCP handle this?" questions kept coming up. Who's allowed to call this tool? What happens if a tool returns 50MB of data? Where are we logging any of this? How do I give Team A read-only access when Team B needs write? Tu