This project provides an AI-powered task management system designed for AI-driven development workflows, specifically integrating with Cursor AI and other editor environments. It aims to streamline the process of breaking down projects into actionable tasks, assigning priorities, and generating code snippets, benefiting developers seeking an AI-assisted approach to project management.

How It Works

Task Master leverages the Claude API for its core AI capabilities, allowing it to parse project requirements (like PRDs) and generate structured tasks. It supports optional integration with the Perplexity API for enhanced search or information retrieval. The system operates via a command-line interface or through editor integrations using Model Control Protocol (MCP), enabling users to interact with the AI for task generation, prioritization, and implementation assistance directly within their development environment.

Quick Start & Requirements

• Installation: npm install -g task-master-ai (global) or npm install task-master-ai (local).
• Prerequisites: Anthropic API key (Claude API). Optional: OpenAI SDK for Perplexity API.
• Setup: MCP integration involves adding a JSON configuration to your editor. CLI setup includes task-master init.
• Documentation: docs directory

Highlighted Details

• Seamless integration with Cursor AI and other editors via MCP.
• AI-driven task generation, prioritization, and code implementation assistance.
• Supports parsing of PRDs and generation of task files.
• Configurable parameters for AI model, tokens, and temperature.

Maintenance & Community

The project is maintained by @eyaltoledano and @RalphEcom. Further community or roadmap information is not explicitly detailed in the README.

Licensing & Compatibility

Licensed under the MIT License with Commons Clause. Commercial use is permitted, but reselling the tool or offering it as a hosted service is restricted.

Limitations & Caveats

The project is described as an AI-driven system, implying potential variability in task generation quality based on the underlying AI models and input data. Troubleshooting steps are provided for initialization issues.