How do I set up Taskmaster with Cursor AI?

Use the one-click MCP install link or manually edit ~/.cursor/mcp.json with your API keys, then enable it in Cursor's MCP settings. Initialize by typing 'Initialize taskmaster-ai in my project' in chat, as detailed in the Quick Start section.

Taskmaster vs Jira for development tasks?

Taskmaster is optimized for AI-driven coding workflows within editors, using chat for task management and PRD parsing. Jira is a broader project management tool with more features like sprint planning, but lacks direct AI integration and MCP support.

Can I use Taskmaster without an internet connection?

Only with Claude Code local models via the Claude Code CLI, which requires no API keys. Most features, like task generation and research, depend on external AI APIs that need internet access and may incur costs.

How to troubleshoot '0 tools enabled' error in Taskmaster?

Restart your editor and double-check that API keys are correctly set in the MCP configuration file. Ensure the TASK_MASTER_TOOLS environment variable is properly configured if using custom tool loading modes.

What editors besides Cursor support Taskmaster?

It supports Windsurf, VS Code, and Q CLI via MCP, with specific configuration paths and JSON structures provided in the README. Each requires setting up mcp.json or equivalent files with API keys.

How to use Claude Code with Taskmaster without API keys?

Install Claude Code CLI, then add Taskmaster via 'claude mcp add taskmaster-ai' with appropriate env settings. In chat, change the main model to 'claude-code/sonnet' to leverage local AI capabilities.

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Claude Task Master

NOASSERTIONJavaScripttask-master-ai@0.43.1

An AI-powered task management system that integrates with Cursor, Windsurf, and other AI code editors via MCP.

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What is Claude Task Master?

Taskmaster is an AI-powered task management system designed for developers using AI-assisted coding environments like Cursor and Windsurf. It integrates via the Model Control Protocol (MCP) to allow natural language task management through chat, automatically breaking down PRDs into development tasks and tracking progress. It solves the problem of disjointed task management in AI-driven workflows by bringing planning and execution into the same conversational interface.

Target Audience

Developers using AI code assistants like Cursor, Windsurf, or Claude Code who want to manage project tasks directly within their editor's chat interface. It's particularly valuable for teams adopting AI-driven development methodologies.

Value Proposition

Developers choose Taskmaster because it eliminates context switching between task management tools and AI coding assistants, provides intelligent task breakdown from PRDs, and offers flexible integration with multiple AI models and editors through the standardized MCP protocol.

Overview

An AI-powered task-management system you can drop into Cursor, Lovable, Windsurf, Roo, and others.

Use Cases

Best For

Managing development tasks directly within Cursor AI's chat interface
Breaking down complex Product Requirement Documents into actionable coding tasks
Teams adopting AI-driven development workflows with multiple model providers
Researching technical topics with project context during development
Optimizing MCP server performance with configurable tool loading
Using Claude Code locally for task management without API keys

Not Ideal For

Developers using non-MCP compatible editors or traditional IDEs without AI chat features
Teams that prefer visual, board-based task management tools like Jira or Trello over chat interfaces
Projects in environments with strict data privacy policies that prohibit external AI API usage
Individuals who prefer lightweight, manual task tracking without the overhead of AI model integration

Pros & Cons

Pros

Seamless AI Editor Integration

Integrates directly with Cursor, Windsurf, and VS Code via MCP, allowing task management through natural language chat without leaving the editor, as shown in the one-click install and configuration guides.

Multi-Model Flexibility

Supports Claude, OpenAI, Gemini, Perplexity, and others via API keys, with configurable main, research, and fallback models for redundancy, enabling seamless switching between providers.

Intelligent Task Generation

Automatically parses PRDs to break down complex requirements into actionable development tasks, reducing manual planning effort and keeping workflows aligned with project goals.

Performance Optimization

Offers configurable tool loading (core, standard, all) to reduce context window usage by up to 70%, improving MCP server performance and token efficiency.

Cons

Complex Setup Process

Requires manual configuration of MCP files across different editors and multiple API keys, with noted troubleshooting issues like '0 tools enabled' that can hinder initial use.

Dependency on External Services

Relies on AI model APIs which incur costs, require internet access, and introduce potential points of failure, limiting offline usability except with Claude Code.

Limited Editor Ecosystem

Only works with MCP-compatible editors; traditional IDEs or editors without MCP support are excluded, restricting its usability in diverse development environments.

Restrictive Licensing

Uses MIT License with Commons Clause, prohibiting selling the software or offering it as a hosted service, which may deter commercial adoption or integration into proprietary platforms.

Frequently Asked Questions

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