Trellio-MCP
Manage entire trello via MCP.
README
trellio-mcp — MCP Server for Trello
<!-- mcp-name: io.github.scaratec/trellio-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
- 46 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, 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, 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
159 scenarios passed, 0 failed, 0 skipped
946 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, 46 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.
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。