原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
PopNx MCP为使用 AI 的人准备的 MCP 服务器 · 用大白话讲清楚

Trello

作者:scaratec版本 0.12.0i★ –i在你的电脑上运行
注册名称io.github.scaratec/trellio-mcp

安装

概览

作者提供的说明(英文原文)

MCP server for Trello — manage boards, lists, cards, attachments and more via Claude or Gemini

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 文档、表格与办公
  • 你需要填写:TRELLO_API_KEY, TRELLO_TOKEN

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 需要你自己填写: TRELLO_API_KEY, TRELLO_TOKEN

标为机密的值是你账户的钥匙。千万不要分享给别人,也不要粘贴到聊天里。

你需要

  • PyPI已安装 Python 的 uv(用于 uvx 命令)

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "trellio": {
      "command": "uvx",
      "args": [
        "trellio-mcp"
      ],
      "env": {
        "TRELLO_API_KEY": "your-value",
        "TRELLO_TOKEN": "your-value"
      }
    }
  }
}

在终端中运行这条命令

claude mcp add trellio --env TRELLO_API_KEY=your-value --env TRELLO_TOKEN=your-value -- uvx trellio-mcp

运行前请先填写空着的值。

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "trellio": {
      "command": "uvx",
      "args": [
        "trellio-mcp"
      ],
      "env": {
        "TRELLO_API_KEY": "your-value",
        "TRELLO_TOKEN": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "trellio": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "trellio-mcp"
      ],
      "env": {
        "TRELLO_API_KEY": "your-value",
        "TRELLO_TOKEN": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上,无需账户。

需要你填写的值

  • TRELLO_API_KEY 机密 必填 env
    Trello API Key (from https://trello.com/power-ups/admin)
  • TRELLO_TOKEN 机密 必填 env
    Trello API Token

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 scaratec 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

与“文档、表格与办公”中的其他服务器比较i

  • 星标数多于此分类中其他 3533 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 3533 个服务器的 8% 更新
  • 基础检查结果等于或优于此分类中其他 3533 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

Trello 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

你需要填写:TRELLO_API_KEY, TRELLO_TOKEN

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(0.12.0)于7个月前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Python (uv)。

有什么可以替代它?

同一分类中有:Agent-Native Calendar, Excel MCP Server, MCP Server for Excel

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Agent-Native Calendar

作者:BuilderIO

Agent-Native Google Calendar - manage events, sync, and public booking

在云端运行★ 7,620MIT2个月前更新
安装

Excel MCP Server

作者:haris-musa

Create and edit Excel files with AI: charts, PivotTables, formulas. No Excel needed.

在你的电脑上运行★ 4,276MIT7天前更新
安装

MCP Server for Excel

作者:sbroenne

Excel automation for AI - Sheets, Power Query, DAX, VBA, Tables, Ranges and more. Windows only.

在你的电脑上运行★ 847MIT4天前更新
安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

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_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

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

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

Accepted weaknesses are recorded separately in docs/limitations/. A limitation there has already been weighed against the clean solution and declined — check the register before proposing a fix for a known-imperfect behaviour.

Testing

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

PYTHONPATH=src .venv/bin/python -m behave
18 features passed, 0 failed, 0 skipped

182 scenarios passed, 0 failed, 0 skipped 1103 steps passed, 0 failed, 0 skipped

dependency_compatibility.feature needs network access: it builds a wheel, installs it into throwaway environments at both ends of the declared mcp range, and drives the resulting server over stdio. It is the only feature that sees a broken dependency declaration — the others import the tool functions against the local .venv. It carries no opt-in tag on purpose: a dependency guard that has to be asked for is not a guard. To run the suite offline, exclude it explicitly:

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

--exclude dependency_compatibility

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/ # 18 BDD feature files │ └── steps/ # Step definitions ├── docs/ │ ├── adr/ # 7 Architecture Decision Records │ ├── limitations/ # Limitation Records (accepted weaknesses) │ ├── tool-design.md # Scenario-driven tool analysis │ └── case-study-bdd-mcp-server.md └── pyproject.toml

Publishing

PyPI
uv build

twine upload dist/trellio_mcp- *

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.

The resulting listing stays empty. Smithery populates an external entry by scanning the server over HTTP; this server is stdio-only (ADR 002), so the scan fails and the entry carries no connection or tool list — even though the publish command reports success. See LIM 0001. Install via pipx or uvx instead.

MCP registry

server.json describes the server for the official MCP registry by static declaration rather than introspection. Keep its two version fields in step with pyproject.toml.

License

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

问 PopNx