trellio-mcp 0.1.1

MCP server for Trello — manage boards, lists, cards, labels, checklists and more

trellio-mcp — MCP Server for Trello

An MCP server that gives Claude Desktop, Claude Code, and Gemini CLI full access to the Trello API. Built on the trellio async client library and the official Python MCP SDK. Developed following the BDD Guidelines v1.8.0.

Features

• 40 MCP tools — 1:1 mapping to trellio methods, plus one composite get_board_overview tool
• 2 resource templates — trello://board/{id} and trello://card/{id} for rich context loading
• 3 prompts — summarize_board, create_sprint, daily_standup as workflow shortcuts
• Built-in auth flow — python -m trello_mcp auth opens the browser, user clicks "Allow", token stored securely
• Structured error handling — Trello API errors are translated into clear, actionable MCP error messages
• stdio transport — runs as a local subprocess, no network surface

Tools

Category	Tools	Count
Discovery	list_boards, search	2
Boards	get_board_overview, create_board, get_board, update_board, delete_board	5
Lists	list_lists, create_list	2
Cards	list_cards, create_card, get_card, update_card, delete_card, add_label_to_card, remove_label_from_card	7
Labels	list_board_labels, create_label, update_label, delete_label	4
Checklists	list_card_checklists, create_checklist, delete_checklist, create_check_item, update_check_item, delete_check_item	6
Comments	list_comments, add_comment, update_comment, delete_comment	4
Members	get_me, list_board_members, get_member	3
Attachments	list_attachments, create_attachment, delete_attachment	3
Webhooks	list_webhooks, create_webhook, get_webhook, update_webhook, delete_webhook	5

Card tools support pos (top/bottom), idLabels (comma-separated), due (ISO 8601), and dueComplete (true/false) on create and update.

Prerequisites

• Python 3.10+
• A Trello API Key (add http://localhost:8095 to Allowed Origins)

Installation

From PyPI (recommended)

pip install trellio-mcp

Or run without installing via pipx or uvx:

pipx run trellio-mcp
uvx trellio-mcp

From source

git clone https://github.com/scaratec/trellio-mcp.git
cd trellio-mcp
python3 -m venv .venv
.venv/bin/pip install -e ".[dev]"

Authentication

Interactive (recommended)

Run the auth command on each machine:

TRELLO_API_KEY=your_api_key trellio-mcp auth

If using pipx run:

TRELLO_API_KEY=your_api_key pipx run trellio-mcp auth

This opens a browser where you authorize the app. The token is captured automatically and stored in ~/.config/trellio-mcp/credentials.json (permissions 0600).

After auth, no environment variables are needed — the server reads stored credentials on startup.

Environment Variables (fallback)

If no stored credentials are found, the server falls back to environment variables:

export TRELLO_API_KEY=your_api_key
export TRELLO_TOKEN=your_token

MCP Client Configuration

Claude Desktop

Add to ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):

{
  "mcpServers": {
    "trello": {
      "command": "pipx",
      "args": ["run", "trellio-mcp"]
    }
  }
}

If using env var auth instead of stored credentials, add:

"env": {
  "TRELLO_API_KEY": "your_api_key",
  "TRELLO_TOKEN": "your_token"
}

Claude Code

Add to ~/.claude/settings.json or project .claude/settings.json:

{
  "mcpServers": {
    "trello": {
      "command": "pipx",
      "args": ["run", "trellio-mcp"]
    }
  }
}

Gemini CLI

Add to ~/.gemini/settings.json:

{
  "mcpServers": {
    "trello": {
      "command": "pipx",
      "args": ["run", "trellio-mcp"]
    }
  }
}

Architecture

MCP Client (Claude / Gemini)
    │ stdio (JSON-RPC)
    ▼
trellio-mcp (FastMCP)
    │ async/await
    ▼
trellio (httpx)
    │ HTTPS
    ▼
Trello API

Key decisions (documented in docs/adr/):

ADR	Decision
001	Python MCP SDK for language alignment with trellio
002	stdio transport — no network attack surface
003	Stored credentials with env var fallback
004	1:1 tool mapping — one tool per trellio method
005	trellio as Git dependency pinned to v1.0.0
006	Tools + Resources + Prompts as MCP capabilities
007	isError=true + structured error content

Testing

The project uses BDD with behave, following the BDD Guidelines v1.8.0.

PYTHONPATH=src .venv/bin/python -m behave

15 features passed, 0 failed, 0 skipped
122 scenarios passed, 0 failed, 0 skipped
732 steps passed, 0 failed, 0 skipped

Test architecture:

• AsyncMock(spec=TrellioClient) — mock at the client boundary, not HTTP
• Persistence validation via mock call records (§4.3)
• Anti-hardcoding via Scenario Outlines with >= 2 variants (§2.3)
• Layer-by-layer failure path enumeration: 11 error scenarios (§4.5)
• Independent spec audit per §13

See Case Study for a detailed account of the BDD-driven development process.

Project Structure

trellio-mcp/
├── src/trello_mcp/
│   ├── __init__.py        # Tool registration
│   ├── __main__.py        # Entry point (server + auth)
│   ├── server.py          # FastMCP instance + client mgmt
│   ├── auth.py            # OAuth flow + credential storage
│   ├── errors.py          # Error translation (ADR 007)
│   ├── tools/             # 10 modules, 40 tools
│   ├── resources.py       # 2 resource templates
│   └── prompts.py         # 3 prompts
├── features/              # 15 BDD feature files
│   └── steps/             # Step definitions
├── docs/
│   ├── adr/               # 7 Architecture Decision Records
│   ├── tool-design.md     # Scenario-driven tool analysis
│   └── case-study-bdd-mcp-server.md
└── pyproject.toml

License

This project is licensed under the GNU General Public License v3.0 — see the LICENSE file for details.