Markdown-first compilation
Point docmd at a folder of Markdown files and compile the source tree into documentation. Basic setup does not require a config file, frontmatter, or a framework.
docmd is an open-source documentation compiler that turns a Markdown source tree into a static documentation site and machine-readable outputs. It is designed for teams serving human readers, search systems, LLMs, coding agents, and knowledge tools from one build pipeline.
docmd is an open-source documentation compiler that turns a folder of Markdown files into a static documentation site and additional machine-readable documentation outputs. It is built for projects that need the same source content to serve human readers as well as search systems, LLMs, coding agents, and knowledge tools.
The tool derives site navigation from the Markdown file structure and does not require a configuration file, frontmatter, or a framework for its basic workflow. Its compiler-oriented approach keeps the source tree and generated outputs in one build pipeline rather than requiring separate website and AI-knowledge stacks.
Beyond the website, docmd can generate an offline search index, llms.txt and llms-full.txt, Open Knowledge Format (OKF) output, sitemap and SEO metadata, robots.txt, Open Graph metadata, an MCP interface for AI agents, and AI assistant context. The source describes these as outputs of the documentation build.
Point docmd at a folder of Markdown files and compile the source tree into documentation. Basic setup does not require a config file, frontmatter, or a framework.
The build produces a static site with navigation generated from the source file structure, making the result suitable for deployment on static hosting.
docmd can generate an offline search index along with sitemap, SEO metadata, robots.txt, and Open Graph metadata for site discovery and sharing.
The same source can produce llms.txt, llms-full.txt, Open Knowledge Format output, and AI assistant context for machine-oriented documentation workflows.
The documented output pipeline includes an MCP interface for AI agents, allowing the documentation project to expose an agent-oriented interface in addition to web pages and files.
The repository documents execution through npx, global npm or pnpm installation, and the ghcr.io/docmd-io/docmd Docker image. The development server uses port 3000 in the quick-start example.
Maintain Markdown files in a source folder and compile them into a navigable static site for users who need to read product or project documentation in a browser.
Use the generated llms.txt, llms-full.txt, or Open Knowledge Format outputs when the same documentation must also be consumed by LLMs, RAG-oriented knowledge systems, or other automated tooling.
Use the documented MCP interface and AI assistant context outputs to make project documentation available to coding agents alongside the human-facing site.
Run the dev command against a Markdown folder, open the local server at port 3000, and iterate on the source before creating a deployment build.
Run the build command and publish the generated static site through a supported static host or a self-managed server such as NGINX or Caddy.
docmd uses a folder of Markdown files. In the basic quick-start workflow, navigation is generated from the file structure, and no configuration file, frontmatter, or framework is required.
The documented outputs include an offline search index, llms.txt, llms-full.txt, Open Knowledge Format output, sitemap and SEO metadata, robots.txt, Open Graph metadata, an MCP interface for AI agents, and AI assistant context.
The quick start uses `npx @docmd/core dev` pointed at a Markdown folder, then opens `http://localhost:3000`. The source also documents global installation with npm or pnpm.
Yes. The documented build command is `npx @docmd/core build`. The source lists Vercel, Cloudflare Pages, Netlify, GitHub Pages, S3, NGINX, Caddy, and other static hosts as deployment options.
The repository quick-start documentation states that docmd requires Node.js 20 or later. A Docker image is also documented as an alternative execution method.
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