TickTick MCP Server: Seamless Integration with Task Management through Model Context Protocol (MCP)

Overview: What is TickTick MCP Server?

The TickTick MCP Server provides a robust and versatile solution for integrating AI applications, such as Claude Desktop, Continue, Cursor, and more, directly into the task management ecosystem provided by TickTick. By leveraging the power of Model Context Protocol (MCP), this server enables seamless interaction between these cutting-edge tools and your existing TickTick setup, allowing you to manage tasks, projects, and other workflows with unprecedented efficiency.

🔧 Core Features & MCP Capabilities

The TickTick MCP Server offers a comprehensive suite of features that cater to various user needs. Through natural language commands and a well-defined API, users can interact with their TickTick accounts using Claude and other MCP clients. Key capabilities include:

• View Projects and Tasks: Access all projects and tasks managed in TickTick.
• Create New Projects and Tasks: Utilize natural language prompts to create both projects and individual tasks.
• Update Task Details: Modify the title, content, dates, priority of existing tasks.
• Complete Tasks: Mark tasks as completed with a simple command.
• Delete Projects and Tasks: Remove unwanted entries from your TickTick account effortlessly.
• Full API Integration: Seamlessly connect to and control all aspects of the TickTick API.

These features are implemented using MCP's standardized protocol, making it easy for developers to create powerful AI applications that interact seamlessly with various data sources and tools.

⚙️ MCP Architecture & Protocol Implementation

At its core, the TickTick MCP Server follows a well-defined architecture consistent with MCP standards. It employs OAuth 2.0 for secure authentication and token management, ensuring seamless access to your TickTick account details without exposing sensitive information. Here's how it works:

1. Authentication Flow: The server initiates an OAuth flow where users grant permission via their TickTick accounts.
2. Data Exchange: Once authorized, the MCP server handles data exchange between the AI application and TickTick’s API.
3. Task Management: The server manages tasks across different projects with precision.

Mermaid Diagram: MCP Protocol Flow

graph TD
    A[AI Application] -->|MCP Client| B[MCP Protocol]
    B --> C[MCP Server]
    C --> D[TickTick API]
    style A fill:#e1f5fe
    style C fill:#f3e5f5

Mermaid Diagram: Data Architecture

graph TD
    A["AI Application"] -->|Requests| B[MCP Client]
    B --> C[Request Handler]
    C --> D[MCP Server]
    D --> E[TickTick API]
    E --> F[Data Source/Tool]
    style A fill:#e1f5fe
    style C fill:#f3e5f5

🚀 Getting Started with Installation

To get up and running quickly, follow these steps:

Prerequisites

• Python 3.10 or higher.
• uv - Fast Python package installer and resolver.
• TickTick account with API access.
• TickTick API credentials (Client ID, Client Secret, Access Token).

Installation Steps

1. Clone the repository:

   git clone https://github.com/jacepark12/ticktick-mcp.git
   cd ticktick-mcp
   

2. Install with uv:

   # Install uv if you don't have it already
   curl -LsSf https://astral.sh/uv/install.sh | sh
   
   # Create a virtual environment
   uv venv
   
   # Activate the virtual environment
   # On macOS/Linux:
   source .venv/bin/activate
   # On Windows:
   .venv\Scripts\activate
   
   # Install the package
   uv pip install -e .
   

3. Authenticate with TickTick:

   # Run the authentication flow
   uv run -m ticktick_mcp.cli auth
   

4. Test your configuration:

   uv run test_server.py
   

💡 Key Use Cases in AI Workflows

1. Task Management Automation: Streamline task creation, updating, and completion using natural language commands.
2. Real-Time Collaboration: Enable real-time collaboration between team members by leveraging AI-generated prompts.

Example Prompts for Claude:

• "Show me all my TickTick projects."
• "Create a new task called 'Finish MCP server documentation' in my work project with high priority."
• "List all tasks in my personal project."
• "Mark the task 'Buy groceries' as complete."
• "Create a new project called 'Vacation Planning' with a blue color."

🔌 Integration with MCP Clients

The TickTick MCP Server is compatible with multiple MCP clients, including:

• Claude Desktop: Fully supported.
• Continue: Supported for tasks and projects but not prompts or conversational commands.
• Cursor: Currently supports only data source interaction.

Compatibility Matrix

MCP Client	Resources	Tools	Prompts
Claude Desktop	✅	✅	✅
Continue	✅	✅	✅
Cursor	❌	✅	❌

📊 Performance & Compatibility Matrix

The server ensures compatibility and performance across different environment configurations. It supports both macOS and Windows operating systems, with optimized performance on modern hardware.

MCP Configuration Sample

{
  "mcpServers": {
    "ticktick": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-ticktick"],
      "env": {
        "API_KEY": "your_api_key"
      }
    }
  }
}

🛠️ Advanced Configuration & Security

For advanced configurations and enhanced security, developers can:

1. Adjust Environment Variables: Modify the .env file to change authentication credentials or server parameters.
2. Secure User Credentials: Store sensitive data securely using environment variables or secure vault tools.

❓ Frequently Asked Questions (FAQ)

Q: How does the TickTick MCP Server enhance AI applications?

A: By enabling seamless integration with your TickTick task management system, users can streamline their workflows and productivity using natural language commands.

Q: What AI applications are supported by this server?

A: The server supports a wide range of MCP clients, including Claude Desktop, Continue, and Cursor. See the compatibility matrix for detailed support levels.

Q: Can I customize the interface or add additional features to the TickTick MCP Server?

A: Yes, the source code is open, allowing users to contribute changes and improvements through pull requests.

Q: How does the server handle token refreshes?

A: The server uses an automated process to refresh tokens when they expire, ensuring continuous access without user intervention.

Q: Are there any limitations or requirements for using this MCP server?

A: You need a TickTick account with API access and appropriate credentials. Additionally, having Python 3.10+ installed is required.

👨‍💻 Development & Contribution Guidelines

Looking to contribute or enhance the TickTick MCP Server? Follow these guidelines:

1. Fork the Repository: Start by forking the project on GitHub.
2. Clone and Set Up: Clone your forked repository and set up the environment as described in the installation section.
3. Run Tests: Ensure that all tests pass before making any changes.
4. Submit Pull Requests: Once your features or bug fixes are ready, submit a pull request for review.

Conclusion

The TickTick MCP Server stands at the intersection of powerful AI applications and efficient task management tools. By providing seamless integration between diverse data sources and AI platforms, this server empowers developers to build complex workflows that enhance productivity and streamline operations. Whether you're using Claude Desktop or another MCP client, the TickTick MCP Server is designed to make your tasks easier and more manageable.

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This documentation highlights the capabilities of the TickTick MCP Server, emphasizing its role in facilitating efficient AI application integration with TickTick task management systems. With comprehensive features, a robust architecture, and extensive compatibility options, this server is crucial for developers looking to enhance their productivity solutions through Model Context Protocol (MCP).