MCP Dev Summit Seoul 2026

In early 2025, as MCP adoption grew, we built our first MCP server for Cloud-Barista, an Apache 2.0 multi-cloud project I maintain. We started with a simple approach: feed REST API docs to an LLM, ask it to generate a server, and connect it to Cloud-Barista.

It worked. Users could provision cloud infrastructure across 10 providers, including AWS, Azure, GCP, Alibaba, and NCP, through LLM clients. It felt like an early glimpse of the Vibe Computing I had imagined.

But the first success was incomplete. The server misused APIs, burned tokens, stopped midway, and sometimes provisioned unintended resources. Imagine an agent creating 1,000 VMs with expensive GPUs by mistake. The real work began when we had to feed it better context and tame it with clearer tool boundaries, workflows, and controls.

This made Multi-Cloud Vibe Computing more concrete. It showed that a useful MCP server needs more than API coverage: context design, tool boundaries, workflow guidance, and safety controls.

This session shares lessons from building and taming an MCP server for a real-world system. It is a hands-on story of learning through mistakes and turning an API wrapper into a useful MCP interface.