mkdocs2confluence 0.12.2

Publish MkDocs Material pages to Confluence Cloud — admonitions, Mermaid diagrams, tabs, page properties and more

mk2conf — MkDocs / Zensical to Confluence

A Python CLI tool that compiles MkDocs-flavoured Markdown into native Confluence storage XHTML and publishes it directly to Confluence Cloud. It is a compiler/transpiler, not an HTML converter — every construct maps to its native Confluence equivalent, so pages look and behave like hand-authored Confluence content.

It also bridges the gap between Confluence reviewers and developers: the sync-comments command turns open Confluence page comments into GitHub pull request review threads, and auto-resolves them in Confluence when the PR is merged.

Zensical compatible — Zensical is the modern successor to MkDocs + Material for MkDocs. Since it uses the same mkdocs.yml format and Python Markdown extensions, your Zensical project works with mk2conf today with no changes required.

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Installation

Requires Python 3.12+. The PyPI package is mkdocs2confluence; the CLI command is mk2conf.

pip install mkdocs2confluence
# or, for an isolated install:
pipx install mkdocs2confluence

From source (see Setup.md):

git clone https://github.com/jeckyl2010/mkdocs2confluence.git
cd mkdocs2confluence && uv sync

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GitHub Actions

Publish docs automatically on every push — no local install needed:

- name: Publish docs to Confluence
  uses: jeckyl2010/mkdocs2confluence@v1
  with:
    token: ${{ secrets.CONFLUENCE_API_TOKEN }}

Full workflow — triggers on changes to docs/ or mkdocs.yml:

name: Publish docs

on:
  push:
    branches: [main]
    paths: ['docs/**', 'mkdocs.yml']

jobs:
  publish:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: jeckyl2010/mkdocs2confluence@v1
        with:
          token: ${{ secrets.CONFLUENCE_API_TOKEN }}
          prune: 'true'

Available inputs: token (required), config, version, dry-run, section, page, prune, quiet. See docs/commands.md for details.

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Quick start

# Preview a page locally (no Confluence API calls)
mk2conf preview --page index.md --watch

# Dry-run: see what would be published
mk2conf publish --dry-run

# Publish all nav pages
mk2conf publish

# Export a section to PDF
mk2conf pdf --section Guide --out guide.pdf

# Sync Confluence comments to GitHub PR review threads
mk2conf sync-comments

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Configuration

Add a confluence: block to your mkdocs.yml:

confluence:
  base_url: https://yourorg.atlassian.net
  space_key: TECH
  email: [e-mail]
  token: !ENV CONFLUENCE_API_TOKEN   # never hardcode the token
  parent_page_id: "123456"           # optional root page
  mermaid_render: kroki              # "kroki" (default) | "kroki:https://your-kroki" | "none"
  full_width: true                   # default: true

The confluence: block is also accepted under extra: for MkDocs strict-mode compatibility. The API token is read from token: in mkdocs.yml, then CONFLUENCE_API_TOKEN, then MK2CONF_TOKEN.

Your first publish:

export CONFLUENCE_API_TOKEN=your_api_token_here
mk2conf preview --page docs/index.md --watch   # verify output locally
mk2conf publish --dry-run                       # check the plan
mk2conf publish                                 # go live

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Documentation

docs/commands.md	Full flag reference for all four commands
docs/features.md	Supported Markdown / Material features and known limitations
Setup.md	Development environment setup

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Architecture

Pipeline stages: loader → preprocess → IR → transforms → emitter → publisher.

The publisher is split into two phases:

• planner.py builds a nav-ordered publish plan, compiles pages, and makes the read-side API calls needed to decide create vs update vs skip.
• executor.py applies that plan, performs the write-side API calls, uploads attachments, and wires parent/child relationships in nav order so parent pages always exist before their children.

publisher/pipeline.py remains a compatibility facade that re-exports the public publish surface used by the CLI and tests.

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Development

uv run pytest -q
uv run ruff check src tests
uv run mypy src
uv run vulture src --min-confidence 80