Trello Task Manager Server

A Python MCP server that allows AI applications to manage tasks on a real Trello board.

This project began as a local JSON Task Manager on Day 4. On Day 5, the storage layer was replaced with the Trello REST API while keeping the same MCP tool interface.

Features

The server exposes four MCP tools:

Tool	Action
add_task	Creates a Trello card in the To Do list
list_tasks	Lists active cards from the To Do list
complete_task	Moves a card to the Done list
delete_task	Safely archives a Trello card

Architecture

User request
      ↓
AI application
      ↓
MCP client
      ↓
Trello Task Manager MCP Server
      ↓
Async HTTP client
      ↓
Trello REST API
      ↓
Trello board updated
      ↓
Structured MCP response

The MCP server defines the capabilities exposed to AI clients.

The Trello client handles:

• Authentication
• Asynchronous HTTP requests
• Timeouts
• HTTP errors
• Network failures
• Trello card operations

Project structure

task-manager-mcp/
├── .env.example
├── .gitignore
├── .python-version
├── README.md
├── get_trello_ids.py
├── main.py
├── pyproject.toml
├── trello_client.py
└── uv.lock

Main files

• main.py — Defines the MCP server and its tools
• trello_client.py — Handles Trello REST API communication
• get_trello_ids.py — Discovers the Trello board and list IDs
• .env.example — Documents the required environment variables
• .env — Stores local credentials and is excluded from Git

Requirements

• Python 3.11 or newer
• uv
• Node.js and npx for MCP Inspector
• A Trello account
• A Trello board with the required lists
• Trello API credentials

Trello board structure

Create a board named:

MCP Task Manager

Create these lists:

To Do
In Progress
Done

Tasks are represented as Trello cards.

Installation

Clone the repository:

git clone YOUR_REPOSITORY_URL
cd task-manager-mcp

Install the dependencies:

uv sync

Environment configuration

Create your local .env file from the example:

Copy-Item .env.example .env

Add your private configuration:

TRELLO_API_KEY=your_api_key
TRELLO_TOKEN=your_token
TRELLO_BOARD_ID=your_board_id
TRELLO_TODO_LIST_ID=your_todo_list_id
TRELLO_IN_PROGRESS_LIST_ID=your_in_progress_list_id
TRELLO_DONE_LIST_ID=your_done_list_id

Never commit .env.

The public .env.example file must contain only empty values:

TRELLO_API_KEY=
TRELLO_TOKEN=
TRELLO_BOARD_ID=
TRELLO_TODO_LIST_ID=
TRELLO_IN_PROGRESS_LIST_ID=
TRELLO_DONE_LIST_ID=

Discovering Trello IDs

After adding TRELLO_API_KEY and TRELLO_TOKEN to .env, run:

uv run python get_trello_ids.py

The script finds the board named MCP Task Manager and displays its board and list IDs.

Copy those IDs into .env.

Board and list IDs are configuration identifiers. The API token is the sensitive credential and must never be shared.

Verify the configuration

Run:

uv run python -c "from trello_client import validate_configuration; validate_configuration(); print('Trello configuration is valid')"

Expected output:

Trello configuration is valid

Test the Trello connection

Run:

uv run python -c "import asyncio; from trello_client import trello_request; result = asyncio.run(trello_request('GET', '/members/me', params={'fields': 'username'})); print('Connected to Trello as:', result['username'])"

Run with MCP Inspector

Start the server through MCP Inspector:

uv run mcp dev main.py

Connect to the server and select List Tools.

The following tools should appear:

add_task
list_tasks
complete_task
delete_task

Tool examples

Add a task

Tool:

add_task

Input:

{
  "title": "Prepare Day 6 MCP article",
  "description": "Add resources and reusable prompts"
}

The server creates a card in the Trello To Do list.

List tasks

Tool:

list_tasks

Input:

{}

This returns the active cards from the configured To Do list.

Complete a task

Tool:

complete_task

Input:

{
  "card_id": "your-trello-card-id"
}

The card moves from its current list to Done.

Delete a task

Tool:

delete_task

Input:

{
  "card_id": "your-trello-card-id"
}

The server archives the card instead of permanently deleting it.

Archiving is safer because the card remains recoverable through Trello.

Structured responses

Trello returns large card objects containing internal metadata.

The MCP server returns only the useful fields:

{
  "id": "trello-card-id",
  "title": "Prepare Day 6 MCP article",
  "description": "Add resources and reusable prompts",
  "completed": false,
  "url": "https://trello.com/c/..."
}

This creates a stable boundary between Trello and MCP clients.

Error handling

The server handles:

• Missing configuration
• Empty task titles
• Empty card IDs
• Invalid card IDs
• Trello HTTP errors
• Authentication failures
• Network failures
• Request timeouts

Expected failures are converted into clear MCP tool errors instead of exposing long internal tracebacks.

Security

The following values must never be committed or published:

• Trello API token
• Real .env contents
• Credentials in screenshots
• Credentials in documentation
• Credentials in Git history

Before committing, verify that .env is ignored:

git check-ignore -v .env

If a token is accidentally committed, revoke it immediately and generate a new one.

Local storage versus Trello

Day 4

MCP tool
    ↓
Local Python function
    ↓
tasks.json

Day 5

MCP tool
    ↓
Trello API client
    ↓
Trello REST API
    ↓
Real Trello card

The public tool names remain familiar even though the backend implementation changed completely.

Key lessons

This project demonstrates:

• Building MCP tools with FastMCP
• Connecting MCP to a real external platform
• REST API authentication
• Secure environment-variable configuration
• Asynchronous HTTP requests with httpx
• Request timeouts
• Controlled API error handling
• Structured MCP responses
• Separation between MCP logic and integration logic
• Safe deletion through archiving
• Keeping an external system as the source of truth

Next step

Day 6 will extend this server with:

• MCP resources
• Resource URIs
• Board and card context
• Reusable prompts
• Daily planning workflows
• Weekly task-summary workflows

Day 5 gave the server the ability to act.

Day 6 will give it reusable context and guided workflows.