Trellio-MCP
Provides full access to the Trello API through 46 MCP tools, enabling AI agents to manage boards, lists, cards, labels, checklists, comments, members, attachments, and webhooks programmatically.
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_overviewtool2 resource templates —
trello://board/{id}andtrello://card/{id}for rich context loading3 prompts —
summarize_board,create_sprint,daily_standupas workflow shortcutsBuilt-in auth flow —
python -m trello_mcp authopens the browser, user clicks "Allow", token stored securelyStructured 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 |
| 2 |
Boards |
| 5 |
Lists |
| 4 |
Cards |
| 9 |
Labels |
| 4 |
Checklists |
| 6 |
Comments |
| 4 |
Members |
| 3 |
Attachments |
| 6 |
Webhooks |
| 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 claudeUsing pipx (recommended)
To install globally so the trellio-mcp command is available in your PATH:
pipx install trellio-mcpAlternatively, 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-mcpFrom 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 authIf using on-the-fly execution (pipx run):
TRELLO_API_KEY=your_api_key pipx run trellio-mcp authThis 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_tokenMCP 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 APIKey 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 |
|
Testing
The project uses BDD with behave, following the BDD Guidelines v1.8.0.
PYTHONPATH=src .venv/bin/python -m behave17 features passed, 0 failed, 0 skipped
163 scenarios passed, 0 failed, 0 skipped
970 steps passed, 0 failed, 0 skippedTest architecture:
AsyncMock(spec=TrellioClient)— mock at the client boundary, not HTTPPersistence 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.tomlPublishing
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-mcpAlso 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.
Maintenance
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