Configuration

Before getting started with Task Master, you’ll need to set up your API keys. There are a couple of ways to do this depending on whether you’re using the CLI or working inside MCP. It’s also a good time to start getting familiar with the other configuration options available — even if you don’t need to adjust them yet, knowing what’s possible will help down the line.

API Key Setup

Task Master uses environment variables to securely store provider API keys and optional endpoint URLs.

MCP Usage: mcp.json file

For MCP/Cursor usage: Configure keys in the env section of your .cursor/mcp.json file.

.env

{
	"mcpServers": {
		"task-master-ai": {
			"command": "npx",
			"args": ["-y", "task-master-ai"],
			"env": {
				"ANTHROPIC_API_KEY": "ANTHROPIC_API_KEY_HERE",
				"PERPLEXITY_API_KEY": "PERPLEXITY_API_KEY_HERE",
				"OPENAI_API_KEY": "OPENAI_API_KEY_HERE",
				"GOOGLE_API_KEY": "GOOGLE_API_KEY_HERE",
				"XAI_API_KEY": "XAI_API_KEY_HERE",
				"OPENROUTER_API_KEY": "OPENROUTER_API_KEY_HERE",
				"MISTRAL_API_KEY": "MISTRAL_API_KEY_HERE",
				"AZURE_OPENAI_API_KEY": "AZURE_OPENAI_API_KEY_HERE",
				"OLLAMA_API_KEY": "OLLAMA_API_KEY_HERE",
				"GITHUB_API_KEY": "GITHUB_API_KEY_HERE"
			}
		}
	}
}

Optimize Context Usage: You can control which Task Master MCP tools are loaded using the TASK_MASTER_TOOLS environment variable. This helps reduce LLM context usage by only loading the tools you need.

Options:

• core or lean (default) - 7 essential tools
• standard - 15 commonly used tools
• all - All 36 tools

Example:

"env": {
  "TASK_MASTER_TOOLS": "standard",
  "ANTHROPIC_API_KEY": "your_key_here"
}

See the MCP Tools documentation for details.

CLI Usage: .env File

Create a .env file in your project root and include the keys for the providers you plan to use:

.env

# Required API keys for providers configured in .taskmaster/config.json
ANTHROPIC_API_KEY=sk-ant-api03-your-key-here
PERPLEXITY_API_KEY=pplx-your-key-here
# OPENAI_API_KEY=sk-your-key-here
# GOOGLE_API_KEY=AIzaSy...
# AZURE_OPENAI_API_KEY=your-azure-openai-api-key-here
# etc.

# Optional Endpoint Overrides
# Use a specific provider's base URL, e.g., for an OpenAI-compatible API
# OPENAI_BASE_URL=https://api.third-party.com/v1
#
# Azure OpenAI Configuration
# AZURE_OPENAI_ENDPOINT=https://your-resource-name.openai.azure.com/ or https://your-endpoint-name.cognitiveservices.azure.com/openai/deployments
# OLLAMA_BASE_URL=http://custom-ollama-host:11434/api

# Google Vertex AI Configuration (Required if using 'vertex' provider)
# VERTEX_PROJECT_ID=your-gcp-project-id

What Else Can Be Configured?

The main configuration file (.taskmaster/config.json) allows you to control nearly every aspect of Task Master’s behavior. Here’s a high-level look at what you can customize:

You don’t need to configure everything up front. Most settings can be left as defaults or updated later as your workflow evolves.

View Configuration Options

Models and Providers

• Role-based model setup: main, research, fallback
• Provider selection (Anthropic, OpenAI, Perplexity, etc.)
• Model IDs per role
• Temperature, max tokens, and other generation settings
• Custom base URLs for OpenAI-compatible APIs

Global Settings

• logLevel: Logging verbosity
• debug: Enable/disable debug mode
• projectName: Optional name for your project
• defaultTag: Default tag for task grouping
• defaultSubtasks: Number of subtasks to auto-generate
• defaultPriority: Priority level for new tasks

API Endpoint Overrides

• ollamaBaseURL: Custom Ollama server URL
• azureBaseURL: Global Azure endpoint
• vertexProjectId: Google Vertex AI project ID
• vertexLocation: Region for Vertex AI models

Tag and Git Integration

• Default tag context per project
• Support for task isolation by tag
• Manual tag creation from Git branches

State Management

• Active tag tracking
• Migration state
• Last tag switch timestamp

For advanced configuration options and detailed customization, see our Advanced Configuration Guide page.