2026.09.20
MrDoc: A Self-Hosted Document System for Individuals and Small Teams
MrDoc organizes documents, wikis, knowledge, and notes around projects, with Markdown, collaboration, permissions, version history, an API, and AI-related features. Review deployment and data-handling needs before adoption.
What it is for
MrDoc is a Python-based online document system aimed at individuals and small teams managing documents, wikis, knowledge, and notes. Its positioning centers on private deployment, with content organized around projects. This makes it relevant to users who want to keep documentation in an environment they control. The repository identifies the project as GPL-3.0 licensed and not archived.
Who may benefit
Individuals can use it for technical notes, reference material, and a searchable personal knowledge base. Small teams can create project spaces, add collaborators, and choose different visibility modes. Teams with an established need for structured documentation, permissions, and revision control may find the project-based model useful.
The supplied repository materials do not establish capacity, performance, audit, or compliance guarantees. Organizations with strict regulatory requirements, complex identity structures, or large-scale concurrency should therefore perform their own evaluation rather than relying on the project description alone.
Documented capabilities
The README describes project-based document management with project, document, template, image, and attachment modules. Markdown editing is supported, along with table pasting, mind maps, flowcharts, and sequence diagrams. The reading interface is described as offering hierarchical navigation, font adjustments, mobile reading optimization, and PDF and ePub export.
Projects can be configured as public, private, visible to specified users, or visible through an access code. A project may have one creator and multiple collaborators with configurable collaboration permissions. Documents support historical version viewing, difference comparison, and restoration. The account-token API can retrieve collections, upload images, and create documents. The v0.9.9 release also notes a kw search parameter for collection document-list retrieval.
The README lists entry points for the Web version, Windows/macOS/Linux desktop clients, an Android app, Chromium and Firefox browser extensions, and an Obsidian plugin. It also mentions AI chat and AI-assisted document writing. The supplied sources do not confirm the models, providers, costs, retention policies, or offline behavior involved.
Adoption and deployment considerations
The README presents Docker Compose and Python/Django deployment paths, and says that database configuration, migrations, and administrator creation are required. Before production use, operators should independently verify reverse-proxy, domain, HTTPS, email, database, media, and attachment-storage requirements; the supplied material does not provide a complete reference architecture or recommended resource profile.
Documents, images, attachments, and API credentials require an operational data-governance plan. Define backup and restore procedures, access controls, and token rotation, then validate uploads, exports, and revision recovery against your own requirements. Permission modes are documented features, not evidence of an independent security audit; no such audit or performance benchmark is provided in the sources.
If AI features are enabled, confirm how model connections work, whether sensitive content leaves the deployment, how logs are retained, and whether administrators can disable the functions. The official v0.9.9 release was published on January 4, 2026, and lists Docker startup-script improvements, login and registration changes, local storage of externally pasted images, and fixes. Operators should still review the release notes before upgrading.
Sources
Sources checked: 2026-09-20