md-to-adf 1.0.1

Convert Markdown to Atlassian Document Format (ADF) and upload to Confluence

md-to-adf

Convert Markdown to Atlassian Document Format (ADF) and publish to Confluence Cloud.

What it does

md-to-adf takes a Markdown file and converts it to the JSON-based Atlassian Document Format (ADF) that Confluence Cloud requires for its REST API. It handles headings, paragraphs, bold/italic/code inline formatting, fenced code blocks, bullet and ordered lists, blockquotes, horizontal rules, tables, and Mermaid diagrams. Once converted, the built-in upload command creates or updates a Confluence page in a single step, so you can keep documentation in version control and push it to Confluence with one command.

Install

pip

pip install md-to-adf

npm (installs the Python package via pip automatically)

npm install -g md2adf

Homebrew

brew tap imzak31/md-to-adf
brew install md-to-adf

Quick start

Convert a Markdown file to ADF JSON:

md-to-adf convert docs/my-page.md

Convert and write to a file:

md-to-adf convert docs/my-page.md --output my-page.adf.json

Convert and validate the output:

md-to-adf convert docs/my-page.md --validate

Upload to Confluence:

md-to-adf upload docs/my-page.md \
  --title "My Page" \
  --space ENG \
  --parent 12345

Upload using environment variables (no flags needed after setup):

export MD_TO_ADF_DOMAIN=myorg.atlassian.net
export MD_TO_ADF_EMAIL=[e-mail]
export MD_TO_ADF_TOKEN=my-api-token
export MD_TO_ADF_SPACE=ENG

md-to-adf upload docs/my-page.md --title "My Page"

Setup

Run the interactive wizard to store your Confluence credentials once:

md-to-adf init

The wizard prompts for your Confluence domain, email address, and API token, then writes them to ~/.md-to-adf/config.toml. After running init, the upload command works without any flags.

To generate a Confluence API token, visit: https://id.atlassian.com/manage-profile/security/api-tokens

Configuration

Config file location: ~/.md-to-adf/config.toml

Example config file:

[confluence]
domain = "myorg.atlassian.net"
email = "[e-mail]"
token = "my-api-token"
space_key = "ENG"

[mermaid]
strategy = "auto"

Settings reference

Setting	Config key	Env var	CLI flag
Domain	confluence.domain	MD_TO_ADF_DOMAIN	--domain
Email	confluence.email	MD_TO_ADF_EMAIL	--email
Token	confluence.token	MD_TO_ADF_TOKEN	--token
Space	confluence.space_key	MD_TO_ADF_SPACE	--space
Mermaid	mermaid.strategy	MD_TO_ADF_MERMAID	--mermaid

Priority: CLI flags > env vars > config file > defaults

CLI Commands

init — Interactive setup wizard

md-to-adf init

Prompts for Confluence credentials and writes ~/.md-to-adf/config.toml.

---

convert — Convert Markdown to ADF

md-to-adf convert <file> [options]

Option	Description
--output FILE	Write ADF JSON to FILE instead of stdout
--validate	Validate the ADF output after conversion
--mermaid STRATEGY	Mermaid handling: auto, macro, image, code

Examples:

# Print ADF JSON to stdout
md-to-adf convert README.md

# Save to file and validate
md-to-adf convert docs/guide.md --output guide.adf.json --validate

---

upload — Upload to Confluence

md-to-adf upload <file> [options]

Option	Description
--title TEXT	Page title (default: filename stem)
--space KEY	Confluence space key
--parent ID	Parent page ID
--domain HOST	Confluence domain
--email EMAIL	Atlassian account email
--token TOKEN	Atlassian API token
--mermaid STRATEGY	Mermaid handling strategy

Examples:

# Upload using config file credentials
md-to-adf upload docs/architecture.md --title "Architecture Overview"

# Upload to a specific space with a parent page
md-to-adf upload docs/guide.md \
  --title "User Guide" \
  --space ENG \
  --parent 98765

---

validate — Validate ADF JSON

md-to-adf validate <file>

Validates a Markdown file (by converting first) or a raw ADF JSON file against the ADF schema.

md-to-adf validate docs/my-page.md
md-to-adf validate output.adf.json

---

spaces — List Confluence spaces

md-to-adf spaces

Lists all spaces accessible with your configured credentials. Useful for finding space keys.

Mermaid Support

Mermaid diagrams in fenced code blocks (```mermaid) are handled according to the selected strategy:

Strategy	Description
auto	Use macro if the Mermaid for Confluence app is installed, otherwise fall back to code
macro	Render as a Confluence Mermaid macro (requires the Mermaid app)
image	Render the diagram to a PNG and attach it to the page
code	Preserve the diagram source as a code block

Set the strategy in config, env var, or per-command:

md-to-adf upload diagram.md --mermaid image

Claude Code Skill

md-to-adf ships a Claude Code skill that lets you upload the current file to Confluence from inside your editor with a single slash command.

Install the skill:

# Copy the skill to your Claude Code skills directory
cp -r /path/to/md-to-adf/skill ~/.claude/skills/md-to-confluence

Or install via the package (after pip install md-to-adf):

md-to-adf-install-skill

Use the skill inside Claude Code:

/md-to-confluence

The skill reads the current file, calls md-to-adf upload, and reports the resulting Confluence URL.

Python Library API

You can use md-to-adf as a library in your own Python projects:

from md_to_adf import convert, validate

# Convert Markdown string to ADF dict
markdown = "# Hello\n\nThis is **bold** text."
adf = convert(markdown)
print(adf)  # {"version": 1, "type": "doc", "content": [...]}

# Validate an ADF dict
errors = validate(adf)
if errors:
    print("Validation errors:", errors)
else:
    print("Valid ADF document")

Upload programmatically:

from md_to_adf import convert
from md_to_adf.confluence.auth import build_token_auth_header
from md_to_adf.confluence.client import ConfluenceClient

adf = convert(open("docs/page.md").read())

auth = build_token_auth_header("[e-mail]", "my-api-token")
client = ConfluenceClient("myorg.atlassian.net", auth)

result = client.create_page(adf, space_key="ENG", title="My Page")
print(f"Published: https://myorg.atlassian.net/wiki{result['_links']['webui']}")

Contributing

1. Fork the repository and create a feature branch.
2. Install development dependencies: pip install -e ".[dev]"
3. Run the test suite: pytest tests/ -v
4. Ensure all tests pass and add tests for new functionality.
5. Open a pull request with a clear description of the change.

The test suite covers the converter, validator, CLI, and Confluence client (with mocked HTTP). New features should include unit tests.

License

MIT — see LICENSE.