Blume Framework Turns Markdown Folders Into AI-Ready Documentation


TL;DR

  • Core Release: Blume 1.0.3 is an MIT-licensed framework that turns Markdown or MDX folders into documentation sites.
  • AI Outputs: It produces Astro-based static pages, machine-readable llms.txt files, optional Ask AI, and four read-only Model Context Protocol tools.
  • Deployment Boundary: Node.js 22.12 or newer is required, while request-time AI features also need server output and a supported adapter.
  • Adoption Test: Teams must decide whether Blume’s generated scaffold and agent access outweigh the operating burden of its interactive features.

Developer Hayden Bleasel has introduced Blume, an MIT-licensed documentation framework that turns Markdown folders into Astro documentation sites for readers and AI tools.

Markdown or MDX, meaning Markdown with embedded JSX-style components, serves as one content set for people and software. Blume builds static pages and exposes raw Markdown at any .md URL, plus llms.txt and llms-full.txt, Copy as Markdown, Open in chat, an optional Ask AI interface, and a hosted Model Context Protocol (MCP) server. MCP lets compatible AI clients call structured tools to search and retrieve documentation.

Blume needs Node.js 22.12 or newer and one Markdown or MDX file. Request-time Ask AI and MCP functions require server output through a Vercel, Netlify, Node, or Cloudflare adapter. Static pages can remain on static hosting, but interactive AI access brings server operations back into the workflow.

How Blume Hides the App Scaffold

Blume’s command-line interface loads blume.config.ts, scans content into a graph, and generates a hidden Astro project under .blume/. Running blume build outputs static HTML to dist/, without requiring users to configure Astro or Tailwind first. During regeneration, Blume rewrites only changed files, keeping authored pages separate from generated application code.