Function calling locks you into one LLM vendor. MCP gives you a universal protocol. The choice seems equal until you're maintaining five integrations.
LLMs choose tools based on descriptions. Bad descriptions mean wrong tool selection. Quality scoring reveals the gap between demo and production.
MCP servers are attack surfaces that LLMs hit autonomously. Every zero-trust principle applies, but most teams treat them like internal microservices.
You already have the business logic. The hard part isn't code — it's writing tool descriptions that LLMs can actually use. Here's the shortest path.
Why the Model Context Protocol is the biggest shift in how software talks to software since REST APIs. And why most people haven't noticed yet.
MCP servers look like they're working until you check the data. 40% tool selection errors, silent failures, cost surprises. Monitoring changes everything.
Everyone is racing to give AI agents access to their systems. Almost nobody is asking what happens when those agents get manipulated. This is the security crisis hiding in plain sight.
Great infrastructure disappears. The best MCP tooling shouldn't require you to think about MCP tooling. Here's what invisible developer tools look like in the age of AI agents.
Most MCP servers are built like REST APIs with extra steps. That's the wrong mental model. Here's how to think about MCP tools the way LLMs actually consume them.
There's no standard for MCP server quality. No benchmark. No score. That's a massive problem hiding in plain sight, and it's holding back the entire ecosystem.