Trello MCP Server for Claude Code

A Model Context Protocol (MCP) server that integrates Trello with Claude Code, providing advanced project planning and task management capabilities with intelligent task analysis.

Features

🎯 Core Task Management

• Create, read, update, and delete tasks across Trello boards and lists

• Automatic board setup with standard lists (To Do, In Progress, Done)

• Priority management with visual indicators

• Due date handling with natural language support ("tomorrow", "next week")

• Status tracking that maps to Trello list positions

🧠 Intelligent Task Analysis

• Complexity assessment (simple/moderate/complex) based on content analysis

• Vague task detection using natural language processing

• Automatic task splitting for overly complex tasks

• Clarity validation with generated clarifying questions

• Board-wide analysis with focused reporting

🔧 Advanced Features

• Batch operations for efficient task management

• Natural language due dates (today, tomorrow, next week)

• Priority-based task organization

• Comprehensive task filtering by status, priority, or due date

• Real-time task intelligence during creation

Installation

1. Clone and setup the project:

   git clone <repository-url>
   cd trello-mcp-server
   npm install

2. Configure Trello API credentials:

   • Copy .env.example to .env

   • Get your Trello API key from: https://trello.com/app-key

   • Generate an API token by visiting: https://trello.com/1/authorize?expiration=never&scope=read,write&response_type=token&name=Claude%20Code%20MCP&key=YOUR_API_KEY

   • Update .env with your credentials:

     TRELLO_API_KEY=your_api_key_here
     TRELLO_API_TOKEN=your_api_token_here
     DEFAULT_TRELLO_BOARD_ID=optional_default_board_id

3. Build the server:

   npm run build

Claude Code Integration

Project-Level Configuration (Recommended)

Create .mcp.json in your project root:

{
  "mcpServers": {
    "trello": {
      "command": "node",
      "args": ["/path/to/trello-mcp-server/build/index.js"],
      "env": {
        "TRELLO_API_KEY": "your_api_key",
        "TRELLO_API_TOKEN": "your_api_token",
        "DEFAULT_TRELLO_BOARD_ID": "your_default_board_id"
      }
    }
  }
}

Global Configuration

Add to your Claude Code configuration:

claude mcp add-json '{
  "command": "node",
  "args": ["/path/to/trello-mcp-server/build/index.js"],
  "env": {
    "TRELLO_API_KEY": "your_api_key",
    "TRELLO_API_TOKEN": "your_api_token"
  }
}'

Usage Examples

Basic Task Management

// List available boards
await trello_list_boards();

// Setup a board with default lists
await trello_setup_board({ boardId: "board_id" });

// Create a task with intelligence
await trello_create_task({
  boardId: "board_id",
  title: "Implement user authentication",
  description: "Create login/logout functionality with JWT tokens",
  priority: "high",
  dueDate: "next week"
});

// Update task status (automatically moves between lists)
await trello_update_task({
  cardId: "card_id",
  status: "in_progress"
});

Intelligent Task Analysis

// Analyze entire board for improvements
await trello_analyze_board({
  boardId: "board_id",
  focusArea: "vague" // or "complex", "overdue", "all"
});

// Get clarifying questions for a vague task
await trello_clarify_task({
  cardId: "card_id"
});

// Split a complex task into smaller ones
await trello_split_task({
  cardId: "card_id",
  autoCreate: true // Automatically create the suggested splits
});

Advanced Filtering

// Get tasks by status
await trello_get_tasks({
  boardId: "board_id",
  status: "in_progress"
});

// Get tasks from specific list
await trello_get_tasks({
  boardId: "board_id",
  listName: "To Do"
});

Available Tools

Task Intelligence Features

Complexity Detection

The system automatically identifies task complexity based on:

• Content length and sentence structure

• Technical keywords (API, database, authentication, etc.)

• Multiple action verbs indicating compound tasks

• Implementation complexity indicators

Vague Task Detection

Automatically flags tasks containing:

• Unclear language ("somehow", "figure out", "handle", etc.)

• Missing acceptance criteria

• Ambiguous requirements

• Incomplete implementation details

Automatic Task Splitting

Intelligently suggests task splits based on:

• Natural language conjunctions ("and", "or")

• Comma-separated requirements

• Complex implementation patterns

• Standard development phases (planning, implementation, testing)

Development

Running in Development Mode

npm run dev  # Watches for changes and rebuilds

Testing with MCP Inspector

npx @modelcontextprotocol/inspector build/index.js

Environment Variables

• TRELLO_API_KEY - Your Trello API key (required)

• TRELLO_API_TOKEN - Your Trello API token (required)

• DEFAULT_TRELLO_BOARD_ID - Default board for operations (optional)

Architecture

Components

• TrelloClient: Core API wrapper with full CRUD operations

• TaskAnalyzer: Natural language processing for task intelligence

• MCP Server: Protocol implementation with comprehensive tool handlers

Data Flow

Claude Code → MCP Client → Trello MCP Server → Trello REST API → Trello Boards

Task State Mapping

• Pending → "To Do" list

• In Progress → "In Progress" list

• Completed → "Done" list

Contributing

1. Fork the repository

2. Create a feature branch

3. Add tests for new functionality

4. Submit a pull request

License

MIT License - see LICENSE file for details.

Support

For issues and feature requests, please open an issue on GitHub or refer to the Trello API documentation for API-related questions.