A tool for loading Trello boards and converting them to Markdown for AI agents
Project description
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
- Clone the repository
- Change to the project directory
- Install dependencies with uv:
uv pip install -e .
Configuration
- Create a
.envfile in the project's root directory - Add your Trello API keys (see
.env.example)
To obtain Trello API keys:
- Visit https://trello.com/app-key
- Log in with your Trello account
- Copy your API key
- 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:
- Update the version in
pyproject.tomlandtrello_loader/__init__.py - Install the required build tools:
uv pip install build twine
- Build the package:
uv run -m build
- 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
Project details
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