TaskFlow MCP 🌟

Welcome to TaskFlow MCP, a task management Model Context Protocol (MCP) server designed to enhance AI assistants. This project helps break down user requests into manageable tasks, complete with subtasks, dependencies, and notes. It enforces a structured workflow with user approval steps, making task management simpler and more efficient.

Table of Contents

• Features
• Getting Started
• Installation
• Usage
• Contributing
• License
• Links

Features

• Task Management: Break down complex requests into simple tasks.
• Subtasks: Organize tasks into smaller, manageable components.
• Dependencies: Define task dependencies to maintain workflow integrity.
• Notes: Attach notes to tasks for additional context.
• User Approval: Ensure tasks receive user confirmation before proceeding.
• Easy Integration: Designed to work seamlessly with AI assistants.

Getting Started

To get started with TaskFlow MCP, follow the instructions below. You can download the latest release here.

Prerequisites

Make sure you have the following installed:

• Node.js (version 14 or higher)
• npm (Node Package Manager)

Installation

1. Clone the repository:

   git clone https://github.com/Aekkaratjerasuk/taskflow-mcp.git
   

2. Navigate to the project directory:

   cd taskflow-mcp
   

3. Install the required dependencies:

   npm install
   

4. Start the server:

   npm start
   

Now, your TaskFlow MCP server is running and ready to manage tasks.

Usage

Once the server is running, you can interact with it through your AI assistant. Here’s how to utilize the features:

Creating Tasks

To create a new task, send a request to the server with the task details. The server will respond with a unique task ID.

Adding Subtasks

You can add subtasks to any existing task by specifying the parent task ID. This helps in organizing tasks better.

Managing Dependencies

Define dependencies between tasks to ensure they execute in the correct order. The server will handle the logic for you.

Adding Notes

Attach notes to any task for additional context. This is useful for providing background information or instructions.

User Approval

Before a task proceeds, the server will prompt for user approval. This ensures that the user is always in control.

Contributing

We welcome contributions to TaskFlow MCP! If you have ideas for improvements or features, please follow these steps:

1. Fork the repository.
2. Create a new branch for your feature or fix.
3. Make your changes.
4. Submit a pull request.

Please ensure that your code follows our coding standards and includes tests where applicable.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Links

For more information and updates, visit the Releases section. Here, you can find the latest versions and updates for TaskFlow MCP.

Feel free to explore, contribute, and make the most out of TaskFlow MCP. We appreciate your interest and support!