API Documentation Generator from Code
I've spent enough hours copying endpoint names into a Word doc to know exactly why this page exists. Every team hits the same wall eventually. The code changes on Tuesday. The docs still say what was true three sprints ago. And the developer trying to integrate your API has no idea which version is real.
This tool reads your actual codebase and builds the documentation from what's really there, not from a spec file someone forgot to update. We built it because spec-first tools work fine until the spec and the code disagree, and then nobody trusts either one.
The Problem with Manual and Spec First Docs
Most API documentation breaks the same way. Someone writes it once, ships the feature and moves on. Six months later the docs are a museum piece.
Docs Drift Out of Sync With Code
The moment a developer changes a parameter name without updating the reference page, the documentation starts lying. Not on purpose. It just happens because writing docs is the last step in most workflows, and last steps get skipped when deadlines hit.
I've watched this play out on real teams. A field gets renamed in a pull request. The spec file doesn't get touched. Three weeks later, a partner integration breaks in production because their code was built against the old field name still sitting in the published docs.
This is exactly the frustration people vent about on developer forums. On a Reddit thread in r/node, one developer described exactly this cycle and asked for alternatives to expensive hosted doc platforms just to get something that stayed current without babysitting it.
Spec Only Tools Miss Real Implementation Details
An OpenAPI file tells you what an endpoint is supposed to accept. It does not always tell you what actually happens when a request hits an edge case, or what a real response looks like once your database returns null for an optional field.
Tools that generate documentation purely from a Swagger or OpenAPI spec are only as accurate as whoever last edited that spec by hand. If the spec was written before the code, or drifted after it, the documentation inherits every one of those gaps.
Generating documentation directly from your source code closes that gap because the reference comes from what the code actually does, not from a description someone typed into a YAML file weeks ago.
SDK and Multi Language Client Docs Are Hard to Automate
This is the part almost nobody talks about, and it's the exact question that came up unanswered in that same Reddit thread. A developer asked how to document the actual SDK client code generated across multiple languages, the kind of thing you see when an API offers a Python client, a Node client, and a Go client side by side with language specific code samples.
Most spec based generators stop at the endpoint level. They show you the request and response shape, but they don't automatically produce accurate, language specific usage examples for each SDK your team ships.
We built this feature specifically because that gap kept showing up in real developer conversations, not because a competitor already covered it well. If your API ships client libraries in more than one language, this is usually the single biggest documentation task nobody wants to own.
How It Works
Connecting your project takes a few minutes. Understanding what happens after that matters more.
Connect Your Repository
You link your codebase once. From there, the tool has what it needs to start building reference pages without you writing a single line of documentation by hand.
No spec file is required to get started, though if you already maintain an OpenAPI file, it can be used alongside your code for extra context.
AI Reads Your Code, Types, and Comments
The tool scans your routes, your type definitions, and any comments or docstrings you've already written. It pulls parameter names, expected types, and return shapes directly from what your code declares.
For REST endpoints, detection is largely automatic. For GraphQL resolvers, RPC methods, and less conventional patterns, the analysis leans on AI to interpret intent from how the code is structured, since those don't always follow a single predictable format the way REST routes do.
I'll be honest about where this needs a human eye. Auto generated descriptions are a strong first draft. On complex business logic, a quick review from someone who actually built the endpoint still makes the final docs noticeably better.
Docs Generate and Stay in Sync on Every Push
Once connected, documentation regenerates when new code is pushed. That's the entire point of building this from code instead of from a spec someone has to remember to update.
You still control what gets published. Regeneration doesn't mean anything goes live without you reviewing it first, if that's how your team prefers to work.
What You Get
Here's what actually shows up on your documentation pages once everything is connected.
Endpoint Detection Across REST, GraphQL, and RPC
REST endpoints get detected automatically from your routes. GraphQL resolvers and RPC methods get analyzed and translated into readable reference entries, since those patterns vary more from project to project than plain REST routing does.
Request and Response Examples From Real Types
Examples get generated from your actual type definitions and schemas, not from a generic placeholder that looks the same on every documentation site you've ever seen. If your User type has an email field and an optional phone field, the example reflects that structure.
Authentication and Auth Flow Documentation
Your auth flow, required headers, and token handling get documented based on how your code actually implements authentication. This is usually the section developers read first when integrating, and it's the section most likely to be wrong when written manually and never revisited.
SDK and Client Code Documentation Across Languages
If your project ships SDKs in multiple languages, this is where that gets addressed directly instead of being left as a manual task for whoever has time. Each language's client library gets its own usage reference, generated from that language's actual client code rather than a single generic example translated by hand into three different syntaxes.
This is the feature we built specifically because it kept coming up as an open problem in developer communities, and spec only tools generally don't touch it at all.
Full Text Searchable Reference
Every endpoint, parameter, and description is searchable. Developers integrating with your API can find what they need without scrolling through a single long page trying to remember where an endpoint was mentioned.
Works With Your Stack
The tool supports common backend frameworks including Express.js, FastAPI, Django, Rails, Spring Boot, and Go based services. GraphQL and tRPC projects are supported through AI based analysis rather than route pattern matching, since those frameworks structure their APIs differently than REST.
If you already maintain an OpenAPI or Swagger file, it can be brought in alongside your code to add extra context where your code comments are thin.
Type extraction works with TypeScript, JSDoc annotations, and Python type hints. If your project uses a language or framework not listed here, reach out before assuming it won't work. Coverage expands based on real project needs, not a fixed list decided in advance.
API Docs From Code vs Spec Based Generators
It helps to see where this actually sits next to the tools you've probably already tried.
| Approach | How docs get built | Where it falls short |
|---|---|---|
| Code based (this tool) | Reads your actual source code, types, and comments | Complex business logic still benefits from a human review pass |
| Spec based (Swagger, Redoc, similar tools) | Reads an OpenAPI or Swagger file you maintain by hand | Docs are only as current as the last time someone updated the spec |
| AI prompt based (chat style generators) | You describe the API in a prompt and the AI writes docs from that description | Accuracy depends entirely on how complete your description was, not on the real code |
None of these approaches is wrong. They solve different problems. If your team already keeps a spec file perfectly current, a spec based tool works fine. If you don't, and most teams don't, generating from code closes that gap without adding another file to maintain.
Pricing That Doesn't Punish You for a Custom Domain
I get why this section needs to exist. On that same r/node thread, a developer using a well known hosted docs platform mentioned paying close to a hundred dollars a month just to put documentation on their own domain, and another reply mentioned quotes running even higher elsewhere.
That's a real cost for a small team or an independent developer publishing public API docs. A custom domain is not a premium feature. It's how you make your documentation look like it belongs to your product instead of a third party subdomain.
[Confirm actual pricing tiers here before publishing, including whether custom domain access is included in the free or entry paid tier, so this section states your real pricing accurately.]
Frequently Asked Questions
Can this generate docs for SDK client code in multiple languages?
Yes. If your project ships SDKs in more than one language, each client library gets its own usage reference built from that language's actual client code, rather than one generic example rewritten by hand for each language.
Does it work without an OpenAPI spec?
Yes. Documentation generates directly from your source code, so a spec file is not required to get started. If you already maintain an OpenAPI file, it can be added alongside your code for extra context, but it's optional.
How is this different from Swagger or Postman?
Swagger and Postman generally work from a spec file or a saved collection that someone maintains by hand. This tool reads your code directly, so the documentation reflects what your API actually does right now rather than what a spec file says it should do.
Does documentation stay updated automatically?
Documentation regenerates when new code is pushed to your connected repository. You still review and control what gets published, so nothing goes live automatically without your team's approval if that's how you prefer to work.