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ondocs
Open-source Ask AI for your docs, with an MCP server
ondocs adds an Ask AI box to your docs: visitors get a short answer from your pages with citations to the exact section, or "I don't know" when the docs don't cover it, on your own model key. Coding agents get an MCP server (search, fetch, list_pages) and llms.txt from the same index. Plugins for Starlight, Docusaurus and VitePress, guides for Next.js, Fumadocs and Nextra, or one script tag. No vendor, no vector database. MIT licensed.
Hi Product Hunt, I'm Diogo. I built ondocs because docs are written for people to read, but visitors want answers, and coding agents need a way in too. Most Ask AI for docs is a hosted assistant; I wanted one that runs from your own site, on your own key.
ondocs builds one static index with your site. Visitors get a ⌘I Ask dialog that streams a short answer with citations to the exact section, and says "I don't know" without calling the model when the docs don't cover the question. Coding agents get an MCP server (search, fetch, list_pages) that calls no model at all, plus llms.txt and a Markdown copy of every page.
It runs on your own model key (OpenAI, Anthropic, Gemini or any AI SDK provider), with rate limits and a daily budget on by default. Plugins for Starlight, Docusaurus and VitePress, guides for Next.js, Fumadocs and Nextra, or one script tag for any other site.
Ask its own docs, no sign-up: https://ondocs.vercel.app
It's MIT licensed and the roadmap is public. If you try it on a real project, tell me where it breaks.
About ondocs on Product Hunt
“Open-source Ask AI for your docs, with an MCP server”
ondocs was submitted on Product Hunt and earned 3 upvotes and 1 comments, placing #142 on the daily leaderboard. ondocs adds an Ask AI box to your docs: visitors get a short answer from your pages with citations to the exact section, or "I don't know" when the docs don't cover it, on your own model key. Coding agents get an MCP server (search, fetch, list_pages) and llms.txt from the same index. Plugins for Starlight, Docusaurus and VitePress, guides for Next.js, Fumadocs and Nextra, or one script tag. No vendor, no vector database. MIT licensed.
On the analytics side, ondocs competes within Open Source, Developer Tools, Artificial Intelligence and GitHub — topics that collectively have 1.1M followers on Product Hunt. The dashboard above tracks how ondocs performed against the three products that launched closest to it on the same day.
Who hunted ondocs?
ondocs was hunted by Diogo Esteves. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of ondocs including community comment highlights and product details, visit the product overview.
Diogo Esteves