5 posts tagged with "Deep Dives"

The Model Context Protocol just got a major upgrade. MCP Apps (SEP-1865) is a new extension that lets MCP servers deliver interactive user interfaces directly to AI applications like Claude, ChatGPT, or Cursor.

This isn't just about pretty visuals. It's about giving your AI tools the ability to show data in ways that actually make sense—charts, tables, dashboards, forms—while maintaining the security and auditability that MCP was built on.

Users would ask Claude to "set up all my integrations," and Claude would call our provisioning tool. Then nothing. Users waited 45 seconds staring at a spinner while our server created API keys, configured webhooks, and set up OAuth clients. Most users gave up after 15 seconds, thinking it failed.

Then someone asked Claude to "clean up old bundles," and Claude dutifully deleted everything from the last 6 months. Because we let it.

We needed streaming for long-running work, chunking for large operations, and approval gates for anything scary. Here's what works.

Our 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 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.