Trello Loader

A tool for loading Trello boards and converting them to structured Markdown files for AI agents.

Features

• Loads Trello boards via the official API
• Converts Trello lists and cards into structured Markdown files
• Preserves important information such as descriptions, checklists, labels, and due dates
• Formats tasks as Markdown ToDo lists, ideal for AI agents

Installation with uv

This project is managed with uv, an ultra-fast Python package manager.

If you don't have uv installed yet, you can install it with the following command:

curl -sSf https://install.astronomer.dev | sh

Or on Windows with:

powershell -c "irm https://install.astronomer.dev | iex"

Project Installation

1. Clone the repository
2. Change to the project directory
3. Install dependencies with uv:

uv pip install -e .

Configuration

1. Create a .env file in the project's root directory
2. Add your Trello API keys (see .env.example)

To obtain Trello API keys:

1. Visit https://trello.com/app-key
2. Log in with your Trello account
3. Copy your API key
4. Generate a token with appropriate permissions

Usage

List all boards

uv run trello-to-md list-boards

Convert a board

uv run trello-to-md convert BOARD_ID

Where BOARD_ID is the ID of the Trello board, which you can find using list-boards.

Options

• --output / -o: Path to the output Markdown file
• --archived / -a: Include archived cards

Example

trello-to-md convert abc123 -o my_tasks.md

Output Format

The generated Markdown file is structured as follows:

# Board Name

Board description, if available

*Created on: YYYY-MM-DD HH:MM*

*Board ID: abc123*

---

## List 1

- [ ] **Card name**
  Card description
  - Checklists:
    - Checklist 1
      - [ ] Item 1
      - [x] Item 2
  - Tags: `Tag1`, `Tag2`
  - Due: YYYY-MM-DD HH:MM
  - [Go to card](https://trello.com/...)

## List 2

- [ ] **Card name 2**
  ...

Publishing to PyPI

If you want to publish this package to PyPI:

1. Update the version in pyproject.toml and trello_loader/__init__.py
2. Install the required build tools:

   uv pip install build twine
   

3. Build the package:

   uv run -m build
   

4. Upload to PyPI:

   uv run -m twine upload dist/*
   

You'll need PyPI credentials to publish the package.

Installation from PyPI

Once published, the package can be installed with:

uv pip install trello-loader

License

MIT