MarkedDocs gives every team, client, or product its own branded knowledge base - written in Markdown, surfaced via a powerful REST API, and ready to connect with any AI workflow through our built-in MCP server.
Trusted by teams shipping great documentation
From writing your first article to powering a fully automated AI support workflow - MarkedDocs has every building block already in place.
Write in the format developers already love. Full CommonMark support with extensions for tables, callouts, code blocks with syntax highlighting, and embedded media. No proprietary lock-in - your content is always portable.
Every client, product, or department gets its own fully isolated knowledge base with a custom URL slug. Independent categories, articles, branding, and access controls - all managed from an intuitive dashboard.
Lightning-fast search across all articles, with highlighted matches and category filtering. Expose it via our pre-built search UI or wire it directly into your own front-end with the Search API endpoint.
Every operation available through the UI - reading, creating, updating articles and categories - is exposed as a clean, versioned REST API. Integrate your CMS, CI/CD pipeline, or custom tooling in minutes.
The Model Context Protocol server lets AI assistants like Claude read, search, and create documentation natively. Build AI-powered support bots, automated doc generation workflows, and context-aware assistants without writing glue code.
Each tenant knowledge base can carry its own logo, colour scheme, and custom domain. Your users see your brand - not ours. Perfect for companies embedding documentation directly into their product experience.
No configuration hell. No infrastructure to manage. Go from sign-up to published knowledge base faster than you can finish your coffee.
Sign up, choose a slug for your knowledge base (e.g. markeddocs.com/your-brand), and configure your branding in under two minutes.
Use the built-in Markdown editor to draft articles and organise them into categories. Import from your existing docs with a simple paste or API push.
Grab your API key and integrate. Embed the search widget, hook into your CI pipeline, or point an AI model at the MCP server - your docs are now alive.
Every piece of functionality in MarkedDocs is reachable via our REST API. But we've gone further: a native Model Context Protocol server means AI assistants can read and write your documentation as naturally as a human editor would.
Whether you're syncing docs from a GitHub repo, auto-generating release notes, or letting Claude answer support questions by searching your knowledge base in real time - the infrastructure is already there.
Read the API docs →Available endpoints
Token auth via POST /api/v1/auth/token/ with Basic auth.
The Model Context Protocol (MCP) is the emerging standard for connecting AI models to real-world data. MarkedDocs ships with a production-ready MCP server out of the box - no setup required.
Configure it once in Claude Desktop, a Cursor workspace, or any MCP-compatible agent, and your AI assistant gains the ability to search articles, retrieve full content, and even draft new documentation directly to your knowledge base.
MCP tools exposed:
search_articles get_article list_categories create_article update_article list_articlesclaude_desktop_config.json
That's it. Your AI assistant now has full access to your docs.
"We replaced a sprawling Notion setup with MarkedDocs in an afternoon. The multi-tenancy alone was worth it - each client now has their own clean knowledge base without any extra overhead."
"The MCP integration was a game-changer. We pointed Claude at our knowledge base and now it can actually answer support tickets with accurate, up-to-date information - no hallucinations, no stale data."
"We auto-publish our release notes from CI straight into MarkedDocs via the API. Our docs are always in sync with the actual product - it's the first time that's ever been true in five years."
No per-seat fees. No article limits on paid plans. Just straightforward pricing that grows with you.
Join the teams who've stopped wrestling with wikis and started building documentation that actually serves their users - and their AI workflows.
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