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Open-source Ask AI for your docs. Cited answers on your own model key, and an MCP server for coding agents, from one index built with your Starlight, Docusaurus or VitePress site. No vendor, no vector database.

For teams that run their own developer docs, at product, API and platform companies, who want Ask AI without a hosted assistant.

Answers with

Ask these docs from your editor, over this site's MCP server:

Website: ondocs.vercel.app, whose docs answer with OpenAI and serve agents at /api/mcp. Formerly ask-my-site (what changed).

Feedback wanted: say where it breaks in the launch feedback thread, see what's next in the roadmap, or pick up a good first issue. If ondocs is useful to you, a star helps other people find it.

<p align="center"> <a href="https://ondocs.vercel.app"><img src=".github/assets/demo.webp" width="100%" alt="The live demo: a question about the docs, a streamed answer with numbered citations, a citation opening the exact section of the FAQ page, then the Ask button on that page answering how to add it to Starlight with the exact config. Last, the one-line setup for Docusaurus, Starlight and any other site."></a> </p>

_{The <a href="https://ondocs.vercel.app">live demo</a>: a streamed answer with citations, one opening the section it came from, then the one-line setups.}

Live demos: Starlight, Docusaurus and VitePress, each a real docs site built with its plugin.

What you get

One index, ask-index.json, built with your site, feeds three things:

• An Ask box for people. A ⌘I dialog that streams a short answer from your model, with numbered citations to the exact section. Most off-topic questions get "I don't know" before the model is called. A page loads only the button; the dialog loads on first use.
• An MCP server for agents. search, fetch and list_pages over the same index, for coding agents and ChatGPT. Agents bring their own model, and keyword search, the default, calls no model at all.
• llms.txt, llms-full.txt and a .md copy of every page, written with the build.

Search runs in memory inside one function you deploy: BM25 and vectors, merged with reciprocal rank fusion.

Pick your setup…