# AI Answers in Docs: Mintlify vs Powerduck

**Short answer:** AI answers help a reader ask questions over the docs, which is a real feature for a large prose library. A spec-driven studio takes a different route: it generates an MCP server so an external agent can call the API correctly, not just answer questions about it. The first reads the docs; the second acts on the API.

## What in-docs answers solve

Navigation and comprehension at scale: a reader asks a question and gets an answer grounded in the documentation instead of searching. That is valuable when the docs are large.

## What an MCP server solves

| Capability | AI answers | MCP server |
| --- | --- | --- |
| Answers questions | Yes | Indirectly |
| Calls the API | No | Yes |
| Grounding | Docs | Contract |
| Acts for the user | No | Yes |

## Why the distinction matters

An answer is informational; a tool call changes state. A generated MCP server lets an agent perform the operation correctly, which is a different capability from explaining it.

## How they fit

Use AI answers for the readers and an MCP server for the agents. They serve two audiences and can coexist.

This is part of the [Powerduck vs Mintlify comparison](https://www.powerduck.com/blog/powerduck-vs-mintlify/). Next, read [export vs lock-in](https://www.powerduck.com/blog/static-doc-export-vs-platform-lock-in/).