DocsAlot
Documentation that works for both humans and AI systems
521 followers
Documentation that works for both humans and AI systems
521 followers
DocsAlot turns scattered help center articles, knowledge base, and developer docs into one source of truth for humans and AI agents. It includes hosted MCP, llms.txt, and skill.md. Your docs show up in AI answers, onboarding gets faster, and agents stop reading stale context.
Connected my Notion help center and the hosted MCP endpoint worked first try, which never happens for me. The llms.txt output was surprisingly clean compared to what I had hacked together before.
DocsAlot
@fatih915449 appreciate you my friend. happy to answer any questions you have.
how does docsabot actually keep things in sync when a source article changes, is it just polling or is there some kind of webhook setup
DocsAlot
@smeyye214197 there are things called triggers, that fire based on certain conditions.
Basedash: AI data analyst
DocsAlot
@kris_lachance thanks Kris, we have a long list of features coming up in the future. More specifically we want to support OpenAPI -> CLI+skill output. Plus lots of observability feature, that allows the docs to self-heal.
The human + AI docs positioning is useful. I’d be curious how you prevent docs from drifting when the AI-facing structure wants very explicit API/context blocks but humans still need a narrative path.
Congrats on the launch. This is a very relevant problem as more teams use AI agents with internal documentation.
I’m also exploring the broader document workflow space, especially around source-grounded outputs for long business documents. Curious how you think about trust and verification when AI agents use documentation as context?
Nice launch! Most teams end up with docs that drift out of date fast.
Quick question, when the API changes (like a breaking change), does the MCP/llms.txt update automatically, or do you need to republish by hand?
Love how DocsAlot bakes llms.txt and skill.md right in instead of treating them as afterthoughts, that little detail shows the team actually understands how AI agents consume docs in practice.