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I Built a Postman for MCP Servers. Here's the Story.

It started in a Jaseci weekly sync. We were discussing the jac-mcp server when someone brought up the idea of an MCP playground — a place to test MCP servers the way Postman lets you test REST APIs. The idea stuck with me, but it didn't feel real until I ran into the problem myself.

I was connecting jac-mcp to GitHub Copilot, trying to understand how tools were being called and what they returned. The answer was: I had no idea. Copilot called tools based on whatever prompt and model it chose, and I was left guessing.

When I started building the jac-shadcn MCP server, I hit the same wall. Testing through an LLM client meant my results depended on the model and prompt, not the server itself. That's not testing. That's hoping.

The Socratic Prompt Method: A Framework for AI-Assisted Development

Every model demo you've ever watched -- Anthropic, OpenAI, whoever -- follows the same script. Someone types a request, the model produces something impressive, the audience applauds. It's a compelling showcase for the model. It's a terrible workflow for an engineer.

I've spent years in compilers, language runtimes, and distributed systems -- the kind of work where handwaving doesn't survive contact with reality. When AI coding assistants arrived, I fell into it like everyone else. The demos make it look so clean.

It took longer than I'd like to admit to recognize the pattern: it's the same thing you see when a developer copies from Stack Overflow without understanding the code. The demo format trains passivity. It optimizes for throughput at the expense of understanding. That tradeoff doesn't hold up in production.