Interview Q and A

This section helps you answer MCP system design questions with practical and production-aware language.

Model answers are intentionally concise so you can adapt them live.

Fundamentals

What is MCP and why does it matter?

MCP is a design approach for exposing context and callable tools to language models through explicit contracts. It matters because it turns vague model behavior into governed, inspectable execution paths.

How does tool routing work in this project?

The API sends prompts to handle_prompt, which calls route to choose a tool and arguments. If a tool is selected, the engine executes it, saves memory, emits traces, and returns output.

System design

How would you scale this server from demo to production?

Add policy-driven routing, persistent memory, and structured observability first. Then introduce queue-based tool execution and autoscaling based on latency and error SLOs.

How do you prevent unsafe tool execution?

Enforce allowlists, per-tool authorization, strict argument validation, and execution timeouts. Treat the tool gateway as the final control boundary regardless of model confidence.

Trade-off matrix

Question	Strong answer pattern	Common weak answer
Deterministic vs model-led routing	Start deterministic and add model logic behind policy checks	"Let the model decide everything"
Memory strategy	Begin with bounded window and promote to retrieval when needed	"Store all history forever"
Observability	Capture route decision, tool args, latency, and outcome per request	"Add logs later"

Production depth

What metrics would you monitor from day one?

Monitor route success rate, tool failure rate, fallback rate, and P95 latency. These metrics directly reflect correctness, reliability, and user experience.

What is your rollback strategy for regressions?

Use staged rollout with golden prompts and automatic rollback on SLO breach. Keep deterministic fallback routes available to preserve baseline service.

--8<-- "_abbreviations.md"