Model Context Protocol
View All TagsOur bundle search tool was taking 12 seconds at P95. Users would ask Claude to "find the Slack integration," watch nothing happen, then ask again. Claude would make the same call twice, wait 24 seconds total, and users would close the tab thinking our service was down.
The tool worked perfectly. It just worked slowly. And in the world of AI assistants, slow might as well be broken.
Here's the thing about schemas: they're basically the contract your model learns from. Get them right, and your tools are easy to find, hard to break, and simple to fix when something goes wrong.
Get them wrong, and you'll spend way too much time debugging why the model keeps calling your tool incorrectly.
I spent two hours staring at Claude Desktop wondering why my MCP server wouldn't connect. The config looked perfect. The server ran fine standalone. But Claude showed no tools. The problem? A single trailing comma in my JSON config that Claude silently ignored.
This is everything I wish the docs had told me upfront.
New to MCP? Start with Introduction to MCP to understand what it is and how it works.
My first MCP server took three hours to get working because I made every possible mistake: no logging, broke stdio with print statements, forgot to restart Claude Desktop, and wondered why nothing worked. Your first one should take 30 minutes.
This is what actually works, with the debugging steps I wish I'd known upfront.
I watched Claude hallucinate API endpoints that didn't exist, confidently call made-up functions, and crash our systems with broken JSON. Then we implemented the Model Context Protocol (MCP), and our error rate dropped from 28% to under 3%.
This is what I wish someone had told me when I started.
