Make your Docs and SDKs agent-ready
Auto-generated llms.txt, an MCP server, and typed SDKs so agents get the right answer the first time.
Shipping agent-ready docs with Fern
The invisible audience is already here
Developers find your API through Claude, Cursor, and ChatGPT. If an agent can't parse your docs or call your SDK, those developers get a hallucinated answer or nothing at all. No error log, no bounce rate, just integrations that never get built.
Agents find your docs
Without an llms.txt, an agent approaching your docs cold may find the right page or it may hallucinate one based on similar APIs in its training data. Fern generates a structured index from day one.
Agents fit your pages in their context
JavaScript-rendered docs return an empty shell. Auth walls return a login form instead of a 401. Bloated HTML burns the token budget. Fern serves clean markdown, sized to fit.
Agents act, not just summarize
MCP server, typed SDKs, and runnable examples turn your docs from reference material into something an agent can execute on behalf of a developer.
How Fern makes you agent-ready
llms.txt and llms-full.txt, generated for you
Every Fern Docs site ships a hierarchical index agents can crawl, with per-page descriptions pulled straight from your frontmatter. 73% of top API docs sites still ship without one.
MCP server in one click
Expose your docs and API as a Model Context Protocol server so Claude, Cursor, and Copilot call your endpoints directly. Developers connect once and the agent does the rest.
Fern SDKs handle pagination automatically — list endpoints return an async iterator you can loop over directly.
Ask Fern in your docs
A RAG-backed assistant grounded in your spec and pages with chunking, vector retrieval, RBAC filtering, and keyword fallback. Answers cite the source so developers verify, not guess.
SDKs agents can call without hallucinating
Typed methods, @example JSDoc on every endpoint, discriminated unions, and forward-compatible enums. Agents read the types and write code that compiles on the first try.
The level of support we receive from Fern is unparalleled; it feels like working with a local internal team rather than an external vendor. Fern's rapid turnaround on complex features demonstrates a deep commitment to our technical success and a true partnership in building our developer ecosystem.
Corey WeathersDeveloper Relations Lead, Deepgram
Agent Score
We built the benchmark for agent-ready docs
Fern Labs partnered with Dachary Carey, creator of the AFDocs standard, to build Agent Score: an open-source benchmark that grades any docs URL 0 to 100 across 22 checks. We run it on our own platform every week and ship the fixes upstream, so every team on Fern moves with the agent ecosystem instead of catching up to it.
Common questions about agent-ready docs and SDKs
Want the full write-up? Read how we built Agent Score.
Make your docs and SDKs agent-ready
A Fern engineer audits your current agent surface, shows you what's missing, and walks through the cutover. No sales pitch, no slide deck.