trellio-mcp

trellio-mcp

scaratec

Complete Trello API access for Claude Desktop with 38 tools, 2 resources, 3 prompts. Manage boards, cards, lists, labels

MCP server providing full access to the Trello API with 48 tools for managing boards, cards, lists, labels, and more. Includes built-in OAuth authentication flow and structured error handling.

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About trellio-mcp

trellio-mcp is a community-built MCP server published by scaratec that provides AI assistants with tools and capabilities via the Model Context Protocol. Complete Trello API access for Claude Desktop with 38 tools, 2 resources, 3 prompts. Manage boards, cards, lists, labels It is categorized under auth security. This server exposes 20 tools that AI clients can invoke during conversations and coding sessions.

How to install

You can install trellio-mcp in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

License

trellio-mcp is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

Tools (20)

list_boards

List all accessible Trello boards

search

Search for boards, cards, and other Trello objects

get_board_overview

Get comprehensive board information including lists and cards

create_board

Create a new Trello board

get_board

Get detailed information about a specific board

trellio-mcp — MCP Server for Trello

License: GPL v3 Python 3.10+ MCP

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

  • 48 MCP tools — 1:1 mapping to trellio methods, plus one composite get_board_overview tool
  • 2 resource templatestrello://board/{id} and trello://card/{id} for rich context loading
  • 3 promptssummarize_board, create_sprint, daily_standup as workflow shortcuts
  • Built-in auth flowpython -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

CategoryToolsCount
Discoverylist_boards, search2
Boardsget_board_overview, create_board, get_board, update_board, delete_board5
Listslist_lists, create_list, update_list, archive_list4
Cardslist_cards, create_card, get_card, update_card, archive_card, unarchive_card, delete_card, add_label_to_card, remove_label_from_card9
Labelslist_board_labels, create_label, update_label, delete_label4
Checklistslist_card_checklists, create_checklist, delete_checklist, create_check_item, update_check_item, delete_check_item6
Commentslist_comments, add_comment, update_comment, delete_comment4
Membersget_me, list_board_members, get_member3
Attachmentslist_attachments, create_attachment, get_attachment, upload_attachment, download_attachment, delete_attachment6
Webhookslist_webhooks, create_webhook, get_webhook, update_webhook, delete_webhook5

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

Smithery

smithery badge

npx @smithery/cli install gupta/trellio-mcp --client claude

Using pipx (recommended)

To install globally so the trellio-mcp command is available in your PATH:

pipx install trellio-mcp

Alternatively, you can run it on-the-fly without installing:

pipx run trellio-mcp

(Note: If you use pipx run, your MCP client configuration must also use pipx as the command and run trellio-mcp as arguments.)

Using pip

pip install 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 to connect your Trello account:

If you installed globally (pipx install or pip install):

TRELLO_API_KEY=your_api_key trellio-mcp auth

If using on-the-fly execution (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/):

ADRDecision
001Python MCP SDK for language alignment with trellio
002stdio transport — no network attack surface
003Stored credentials with env var fallback
0041:1 tool mapping — one tool per trellio method
005trellio as PyPI dependency (>=1.4.0)
006Tools + Resources + Prompts as MCP capabilities
007isError=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
17 features passed, 0 failed, 0 skipped
163 scenarios passed, 0 failed, 0 skipped
970 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 (§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, 48 tools
│   ├── resources.py       # 2 resource templates
│   └── prompts.py         # 3 prompts
├── features/              # 17 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

Publishing

PyPI

uv build
twine upload dist/trellio_mcp-<version>*

Smithery

Namespace is gupta. Update the release after a new PyPI version:

npx @smithery/cli mcp publish "https://github.com/scaratec/trellio-mcp" -n gupta/trellio-mcp

Also update the pinned version in smithery.yaml commandFunction.

License

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

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