I've been building a collaborative docs tool called Docules. The short version: it's a team documentation tool that doesn't have any embedded AI features. I use Claude Code daily, but putting LLMs into every workflow and charging for it is kinda insane. Every docs tool is adding AI auto-complete, AI summaries, "generate a page" buttons. Docules has an API and an MCP server instead, so you connect whatever AI tools you actually want to use. The core product focuses on being a fast, solid docs tool. Real-time collab, fast — no embedded databases or heavy view abstractions, hierarchical docs, drag-and-drop, semantic search, comments, version history, public sharing, SSO, RBAC, audit logs, webhooks, etc. The stack is React, Hono, PostgreSQL, WebSockets. The MCP server is a separate package that exposes search, document CRUD, and comments — so Claude/ChatGPT can work with your docs without us reimplementing a worse version of what they already do. Happy to talk architecture or the MCP integration.

I've been building a collaborative docs tool called Docules. The short version: it's a team documentation tool that doesn't have any embedded AI features. I use Claude code daily, but putting LLM’s into every workflow and charging for it is kinda insane. Every docs tool is adding AI auto-complete, AI summaries, "generate a page" buttons. Docules has an open API and ships an MCP server, so it connects to whatever you want to use LLM-wise. They can read, search, create, and edit documents through the API. The core product is just a docs tool that tries to be good at being a docs tool:

  - Real-time collab with live cursors

  - Fast — no embedded databases or heavy view abstractions slowing things down

  - Hierarchical docs, drag-and-drop, semantic search

  - Comments, version history, public sharing

  - SSO, RBAC, audit logs, webhooks