TickTick MCP Server: Let Your AI Assistant Manage Your Tasks

Stop switching between your AI assistant and TickTick. This MCP server bridges the gap, letting Claude, Cursor, or any MCP-compatible client manage your TickTick tasks directly through natural language.

The Problem: Context Switching Kills Productivity

You're deep in a conversation with Claude about a project, and suddenly you need to:

• Switch to TickTick to create tasks
• Remember all the context from your AI conversation
• Manually translate AI suggestions into actionable tasks
• Switch back and lose momentum

It's a workflow killer that breaks your focus every single time.

The Solution: AI-Native Task Management

This MCP server turns your AI assistant into a task management powerhouse. Your AI can now:

• Create projects and tasks directly from conversation context
• Update existing tasks based on project discussions
• Mark tasks complete as you work through them
• Query your task list to provide context-aware suggestions
• Delete irrelevant tasks without you lifting a finger

Real-World Impact

Before: "I need to create tasks for this new feature... let me open TickTick, create a project, add 8 tasks, set due dates, then come back to continue our conversation."

After: "Create a project called 'User Authentication Refactor' with tasks for database migration, API updates, frontend changes, and testing. Set everything for next Friday."

Your AI handles the entire task creation workflow while you stay focused on the actual work.

Comprehensive Task Operations

The server exposes eight core tools that cover everything you need:

• get_projects - List all your projects for context
• project_details - Deep dive into specific project status
• get_task_details - Examine individual task specifics
• create_project - Spin up new project structures
• create_task - Add tasks with full metadata
• update_task - Modify existing tasks on the fly
• complete_task - Mark tasks done during conversations
• delete_task - Remove obsolete or duplicate tasks

Integration Scenarios

During Code Reviews: "Review the pull request for the payment system and create follow-up tasks for the issues I mentioned."

Project Planning: "Based on our architecture discussion, create a project with tasks for each microservice we need to build."

Daily Standups: "Show me my tasks for today and mark the API documentation as complete."

Bug Triage: "Create tasks for each of these five bugs, prioritize them by severity, and assign them to the mobile project."

Setup for Developers

Getting started requires minimal configuration:

1. Clone and install:

   git clone https://github.com/ekkyarmandi/ticktick-mcp.git
   cd ticktick-mcp
   pip install -r requirements.txt
   

2. Get your TickTick API credentials from the developer portal

3. Authorize your app using the provided OAuth2 flow

4. Configure your environment:

   echo "TICKTICK_API_KEY=your_access_token" > .env
   

5. Start the server:

   python main.py
   

Works With Your Existing Tools

Compatible with any MCP client:

• Claude Desktop for conversational task management
• Cursor IDE for project-based task creation
• Custom applications using MCP SDKs

No vendor lock-in, no proprietary formats - just standard MCP protocol.

Why This Matters

Task management shouldn't require context switching. When your AI assistant understands your project context, it should be able to act on that context directly. This server eliminates the friction between thinking about work and organizing work.

Your AI becomes your project manager, not just your coding assistant.

Ready to streamline your task management workflow? The server is MIT licensed and ready for your specific needs.