LOCAL Task Master - Enhanced AI Client Fork

This is an enhanced fork of the original Task Master project by @eyaltoledano & @RalphEcom. We extend our sincere thanks to the original authors for their excellent work in creating the foundation for this project.

What's New in This Fork?

This fork enhances Task Master with a robust, OpenAI-compatible AI client system that supports both cloud providers and local LLM endpoints. Key improvements include:

• Flexible AI Provider Support: Works with OpenAI, local endpoints (Ollama, LocalAI), and other OpenAI-compatible APIs
• Advanced Configuration Management: Environment-based configuration with support for multiple providers
• Robust Error Handling: Implements retry mechanisms, circuit breakers, and detailed error reporting
• Token Usage Tracking: Built-in monitoring and reporting of token usage across providers
• Streaming Support: Efficient handling of streaming responses with cancellation capabilities
• Provider-Agnostic Interface: Unified API for seamless switching between different AI providers

Requirements

• Ollama installed locally (for running Qwen and other models)
• Optional: API keys for cloud providers (Anthropic, OpenAI, etc.)
• Node.js 18 or higher

Quick Start

Option 1 | MCP (Recommended):

MCP (Model Control Protocol) provides the easiest way to get started with Local Task Master directly in your editor.

1. Install and Start Ollama

# Install Ollama (if not already installed)
# Visit https://ollama.ai for installation instructions

# Pull the Qwen model
ollama pull qwen3

# Start Ollama in a separate terminal
ollama serve

2. Add the MCP config to your editor (Cursor recommended, but it works with other text editors):

{
	"mcpServers": {
		"taskmaster": {
			"command": "npx",
			"args": ["-y", "--package=local-task-master", "local-task-master"],
			"env": {
				"AI_PROVIDER": "ollama",
				"AI_BASE_URL": "http://localhost:11434",
				"MODEL": "qwen3",
				"MAX_TOKENS": "40960",
				"TEMPERATURE": "0.7",
				"DEFAULT_SUBTASKS": "5",
				"DEFAULT_PRIORITY": "medium",
				"DEBUG": "false",
				"LOG_LEVEL": "info",
				"TRACK_USAGE": "true",
				"MAX_RETRIES": "3",
				"RETRY_DELAY": "1000",
				"MAX_CONCURRENT": "4"
			}
		}
	}
}

3. Enable the MCP in your editor

4. Prompt the AI to initialize Local Task Master:

Can you please initialize taskmaster into my project?

5. Use common commands directly through your AI assistant:

Can you parse my PRD at scripts/prd.txt?
What's the next task I should work on?
Can you help me implement task 3?
Can you help me expand task 4?

Option 2: Using Command Line

Installation

# Install globally
npm install -g local-task-master

# OR install locally within your project
npm install local-task-master

Initialize a new project

# If installed globally
task-master init

# If installed locally
npx task-master-init

This will prompt you for project details and set up a new project with the necessary files and structure.

Common Commands

# Initialize a new project
task-master init

# Parse a PRD and generate tasks
task-master parse-prd your-prd.txt

# List all tasks
task-master list

# Show the next task to work on
task-master next

# Generate task files
task-master generate

Environment Variables

In addition to the standard Local Task Master environment variables, this fork supports the following AI-related configurations:

• AI Provider Configuration:

  • ANTHROPIC_API_KEY: Your Anthropic API key
  • OPENAI_API_KEY: Your OpenAI API key
  • AI_BASE_URL: Base URL for custom OpenAI-compatible endpoints
  • OPENAI_MODEL: Default model for OpenAI requests
  • LOCAL_MODEL: Model name for local LLM endpoints

• Performance Settings:

  • MAX_RETRIES: Maximum retry attempts for failed API calls
  • RETRY_DELAY: Initial delay between retries (ms)
  • MAX_CONCURRENT: Maximum concurrent API requests
  • CIRCUIT_BREAKER_THRESHOLD: Failure threshold for circuit breaker

• Monitoring:

  • TRACK_USAGE: Enable/disable token usage tracking
  • USAGE_LOG_PATH: Path for token usage logs
  • DEBUG: Enable detailed debug logging
  • LOG_LEVEL: Set logging verbosity

Documentation

For more detailed information, check out the documentation in the docs directory:

• Configuration Guide - Set up environment variables and customize Local Task Master
• Tutorial - Step-by-step guide to getting started with Local Task Master
• Command Reference - Complete list of all available commands
• Task Structure - Understanding the task format and features
• Example Interactions - Common Cursor AI interaction examples
• AI Client Guide - Detailed guide for the enhanced AI client system
• Provider Integration - Adding support for new AI providers

Troubleshooting

If task-master init doesn't respond:

Try running it with Node directly:

node node_modules/local-task-master/scripts/init.js

Or clone the repository and run:

git clone https://github.com/eyaltoledano/claude-task-master.git
cd claude-task-master
node scripts/init.js

Licensing

Local Task Master is licensed under the MIT License with Commons Clause. This means you can:

✅ Allowed:

• Use Local Task Master for any purpose (personal, commercial, academic)
• Modify the code
• Distribute copies
• Create and sell products built using Local Task Master

❌ Not Allowed:

• Sell Local Task Master itself
• Offer Local Task Master as a hosted service
• Create competing products based on Local Task Master

See the LICENSE file for the complete license text and licensing details for more information.