Docny vs Docsbook: AI-generated docs vs Git-native docs compared
We make Docsbook. This page names the cases where Docny is the better choice, and it quotes no Docny price we could not read on Docny's own site — as of 2026-09-20, docny.io/pricing named a free Hobby plan and a paid, flat-rate Pro plan without publishing the dollar figure where this page's research could read it. Check the current numbers there before you budget.
Side-by-side comparison#
| Feature | Docny | Docsbook |
|---|---|---|
| Best fit | Little or no documentation written yet, or an OpenAPI spec you want turned into reference docs automatically | Docs already live (or you want them to live) as Markdown in a GitHub repo |
| How content starts | Guardian AI scans a GitHub repo, a website URL, or an OpenAPI spec and generates the doc tree, then flags when code and docs drift apart | Reads README.md and docs/ from your repo as written |
| Editing model | MDX for engineers, a WYSIWYG editor for non-technical writers, side by side | Markdown in your repo, reviewed and merged like code |
| OpenAPI ingestion | Yes — generates reference docs directly from an OpenAPI/Swagger spec | Not built in — Docsbook does not generate reference docs from a spec |
llms.txt |
Auto-generated, with llms-full.txt alongside it |
Auto-generated per workspace, with llms-full.txt alongside it |
| MCP server | Included, for Claude, Cursor and other agents to query the docs | Included, OAuth 2.0, on every plan |
| AI chat widget for readers | Built in, described as an in-docs answer engine | Built-in, configurable provider (OpenAI, Anthropic, Gemini, OpenRouter) |
| Code-to-doc drift detection | Built in as a named feature (Guardian AI) | Not an automatic scanner — a Docsbook agent can be asked to reconcile docs against recent commits, but nothing watches continuously on its own |
| AI translation | Not named among Docny's published features, as far as this page's research could read | 15 languages, each indexed separately with hreflang |
| Doc versioning | Not confirmed either way from Docny's own site | Not supported — one version per branch (see Documentation versioning) |
| Pricing model | Free Hobby plan, paid flat-rate Pro plan (figure not published where this page's research could read it) | Pay-as-you-go balance held per project |
How much does each one cost?#
As of 2026-09-20, docny.io/pricing states that Docny "offers a free Hobby plan and flat-rate Pro plan for developer documentation teams," without exposing the Pro price to this page's research — check the current figure there before you budget, since this page cannot move with it.
Docsbook does not sell tiers per site. A Free plan covers branding, navigation, analytics and a custom domain at $0; Pro is $20/month per project with a $20 monthly AI allowance included and overage capped by default; Enterprise is a flat price for unlimited projects, contact sales. Current numbers live on docsbook.io/pricing, generated from the live pricing constants on every request.
How different is the setup?#
Docny starts from whatever you already have: point Guardian AI at a GitHub repo, a live website, or an OpenAPI spec, and it drafts a full doc tree with MDX and a WYSIWYG editor for anyone who does not want to touch Markdown. It then keeps checking that draft against your code and flags when the two drift apart — a real advantage if nobody on the team has the time to notice a stale doc themselves.
Docsbook starts from a repository: connect a GitHub repo and the site redeploys on every push, reading the Markdown you already have (or are willing to write). There is no AI-generation step and no automatic drift scanner running in the background — catching doc drift from a code change is something you ask Docsbook's own agent to do, not something that watches continuously by itself.
How do the AI-search features differ?#
Both platforms auto-generate llms.txt and llms-full.txt, ship an MCP server for agents to query the docs, and build an AI chat widget in rather than treating it as an afterthought. The clearest gap is in how the content itself gets kept current with the product:
- Drift detection — a named, built-in feature of Docny's Guardian AI; on Docsbook, keeping docs in step with the code is a task you hand to an agent yourself, not a background watcher.
- OpenAPI-to-reference generation — Docny turns a spec directly into reference docs; Docsbook does not generate reference content from a spec at all, so a team that only has an OpenAPI spec and no written docs starts closer to done on Docny.
- Translation — Docsbook auto-translates to 15 languages and indexes each locale separately with
hreflang; Docny's own published feature list does not name a translation or multi-language pipeline. See Multi-language documentation SEO for why per-locale indexing matters for search.
When should you choose Docny?#
- You have little or no documentation written anywhere yet, or your best source of truth is an OpenAPI spec rather than hand-written Markdown.
- You want an AI to keep watching for drift between your code and your docs without asking it to check.
- Some of your writers would rather use a WYSIWYG editor than write Markdown by hand.
When should you choose Docsbook?#
- Your docs already live (or you want them to live) as Markdown in a GitHub repository, versioned and reviewable like code.
- You need documentation in more than one language, indexed separately per locale rather than left to a separate pipeline.
- You would rather review what an agent changed in a pull request than let a background scanner rewrite pages on its own.
The bottom line#
Docny is a strong choice if you are starting from little or nothing — including a bare OpenAPI spec — and want an AI to both draft the docs and keep watching for drift on its own. Docsbook is the better fit once your docs already live as Markdown in a Git repo and you want translation and AI discoverability features included by default, with every change reviewed as a pull request rather than applied by a background scanner.