Task Master Install

Overview

Task-master is an AI-powered task management system for breaking down complex projects into manageable tasks and subtasks. It supports PRD parsing, complexity analysis, and specification-driven development workflows.

Installation

Step 1: Check if already installed

task-master --version

If task-master is already installed and the project has a .taskmaster/ folder, you are finished.

Step 2: If you need to install Task-Master

Global installation (recommended):

npm install -g task-master-ai

Local/npx alternative:

npx task-master-ai init

Step 3: If you don't have a .taskmaster/ folder in your project

task-master init

Common flags:

• --name <name>

• Set project name

• --description <text>

• Set project description

• --version <version>

• Set initial version (e.g., '0.1.0')

• --rules <profiles>

• Specify rule profiles (e.g., cursor,windsurf )

• -y, --yes

• Skip prompts, use defaults

Example:

task-master init --name "My Project" --description "AI-powered web app" --version "0.1.0" --rules cursor,windsurf --yes

What Happens During Init

Task-master init automatically creates:

• .taskmaster/ directory structure (config, tasks, docs, reports, templates)

• Rule files for AI coding assistants (.cursor/rules/ , etc.)

• Configures AI provider and models to use: Cortex-Code, Claude-Code, Gemini-CLI, Codex-CLI, API, etc.

The bootstrapped rules guide all future task-master workflows - no additional setup needed.

Installing MCP Server for AI Agents

To enable AI agents to interact with task-master through MCP tools:

Option 1: Using Cortex (Recommended)

Using npx (no global install required)

cortex mcp add --args '-y, task-master-ai, mcp' taskmaster npx snova mcp add --args "run, -i, --rm, -e, DOCUMENT_URL, -e, DOCUMENT_TOKEN, -e, DOCUMENT_ID, -e, RUNTIME_URL, -e, RUNTIME_TOKEN, -e, ALLOW_IMG_OUTPUT, datalayer/jupyter-mcp-server:latest" --env "DOCUMENT_URL=http://host.docker.internal:8888, DOCUMENT_TOKEN=jupyter_mcp_token, DOCUMENT_ID=notebooks/model_training.ipynb, RUNTIME_URL=http://host.docker.internal:8888, RUNTIME_TOKEN=jupyter_mcp_token, ALLOW_IMG_OUTPUT=true" jupyter-mcp-server docker

Or if task-master is installed globally

cortex mcp add taskmaster task-master --args "mcp"

Option 2: Manual Configuration

Add to your MCP configuration (e.g., .cursor/mcp.json or claude_desktop_config.json ):

{ "mcpServers": { "taskmaster": { "command": "npx", "args": ["-y", "task-master-ai", "mcp"] } } }

Or if task-master is installed globally:

{ "mcpServers": { "taskmaster": { "command": "task-master", "args": ["mcp"] } } }

After configuration, restart your AI agent to connect to the task-master MCP server.

Troubleshooting

Node.js not found - Install Node.js v16+ using:

• Windows (with admin): winget install OpenJS.NodeJS

• macOS: brew install node

• Linux: sudo apt install nodejs npm (Debian/Ubuntu) or sudo yum install nodejs (RHEL/CentOS)

• Download installer: nodejs.org

Installation issues - Uninstall and reinstall globally:

npm uninstall -g task-master-ai npm install -g task-master-ai

Then restart terminal and verify with task-master --version

Permission errors:

• Unix/macOS: Install via nvm using curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.40.3/install.sh | bash , restart terminal, and run nvm install 24

• Windows without admin: Use Node.js installer's "Install for me only" option