
trellio-mcp
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.
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 all accessible Trello boards
Search for boards, cards, and other Trello objects
Get comprehensive board information including lists and cards
Create a new Trello board
Get detailed information about a specific board
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
- 48 MCP tools — 1:1 mapping to trellio methods, plus
one composite
get_board_overviewtool - 2 resource templates —
trello://board/{id}andtrello://card/{id}for rich context loading - 3 prompts —
summarize_board,create_sprint,daily_standupas workflow shortcuts - Built-in auth flow —
python -m trello_mcp authopens 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, update_list, archive_list | 4 |
| Cards | list_cards, create_card, get_card, update_card, archive_card, unarchive_card, delete_card, add_label_to_card, remove_label_from_card | 9 |
| 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, get_attachment, upload_attachment, download_attachment, delete_attachment | 6 |
| 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:8095to Allowed Origins)
Installation
Smithery
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/):
| 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 PyPI dependency (>=1.4.0) |
| 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
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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