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任务大师MCP服务器

任务大师是一个专为AI驱动的开发任务设计的任务管理系统，旨在与Cursor AI无缝协作。它通过MCP（模型控制协议）直接在编辑器中运行，支持多种AI模型（如Claude、OpenAI、Google Gemini等），并提供灵活的API密钥配置。用户可以通过命令行或编辑器快速初始化项目、解析需求、生成任务并管理开发流程。任务大师支持多模型切换，推荐使用研究模型以提升任务质量，适用于个人、商业和学术用途。

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README

eyaltoledano%2Fclaude-task-master | Trendshift

Taskmaster logo

Taskmaster: A task management system for AI-driven development, designed to work seamlessly with any AI chat.

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CI GitHub stars npm version License

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By @eyaltoledano & @RalphEcom

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A task management system for AI-driven development with Claude, designed to work seamlessly with Cursor AI.

Documentation

📚 View Full Documentation

For detailed guides, API references, and comprehensive examples, visit our documentation site.

Quick Reference

The following documentation is also available in the docs directory:

Quick Install for Cursor 1.0+ (One-Click)

Add task-master-ai MCP server to Cursor

Note: After clicking the link, you'll still need to add your API keys to the configuration. The link installs the MCP server with placeholder keys that you'll need to replace with your actual API keys.

Claude Code Quick Install

For Claude Code users:

claude mcp add taskmaster-ai -- npx -y task-master-ai

Don't forget to add your API keys to the configuration:

  • in the root .env of your Project
  • in the "env" section of your mcp config for taskmaster-ai

Requirements

Taskmaster utilizes AI across several commands, and those require a separate API key. You can use a variety of models from different AI providers provided you add your API keys. For example, if you want to use Claude 3.7, you'll need an Anthropic API key.

You can define 3 types of models to be used: the main model, the research model, and the fallback model (in case either the main or research fail). Whatever model you use, its provider API key must be present in either mcp.json or .env.

At least one (1) of the following is required:

  • Anthropic API key (Claude API)
  • OpenAI API key
  • Google Gemini API key
  • Perplexity API key (for research model)
  • xAI API Key (for research or main model)
  • OpenRouter API Key (for research or main model)
  • Claude Code (no API key required - requires Claude Code CLI)
  • Codex CLI (OAuth via ChatGPT subscription - requires Codex CLI)

Using the research model is optional but highly recommended. You will need at least ONE API key (unless using Claude Code or Codex CLI with OAuth). Adding all API keys enables you to seamlessly switch between model providers at will.

Quick Start

Option 1: MCP (Recommended)

MCP (Model Control Protocol) lets you run Task Master directly from your editor.

1. Add your MCP config at the following path depending on your editor

| Editor | Scope | Linux/macOS Path | Windows Path | Key | | ------------ | ------- | ------------------------------------- | ------------------------------------------------- | ------------ | | Cursor | Global | ~/.cursor/mcp.json | %USERPROFILE%\.cursor\mcp.json | mcpServers | | | Project | <project_folder>/.cursor/mcp.json | <project_folder>\.cursor\mcp.json | mcpServers | | Windsurf | Global | ~/.codeium/windsurf/mcp_config.json | %USERPROFILE%\.codeium\windsurf\mcp_config.json | mcpServers | | VS Code | Project | <project_folder>/.vscode/mcp.json | <project_folder>\.vscode\mcp.json | servers | | Q CLI | Global | ~/.aws/amazonq/mcp.json | | mcpServers |

Manual Configuration
Cursor & Windsurf & Q Developer CLI (mcpServers)
{
  "mcpServers": {
    "task-master-ai": {
      "command": "npx",
      "args": ["-y", "task-master-ai"],
      "env": {
        // "TASK_MASTER_TOOLS": "all", // Options: "all", "standard", "core", or comma-separated list of tools
        "ANTHROPIC_API_KEY": "YOUR_ANTHROPIC_API_KEY_HERE",
        "PERPLEXITY_API_KEY": "YOUR_PERPLEXITY_API_KEY_HERE",
        "OPENAI_API_KEY": "YOUR_OPENAI_KEY_HERE",
        "GOOGLE_API_KEY": "YOUR_GOOGLE_KEY_HERE",
        "MISTRAL_API_KEY": "YOUR_MISTRAL_KEY_HERE",
        "GROQ_API_KEY": "YOUR_GROQ_KEY_HERE",
        "OPENROUTER_API_KEY": "YOUR_OPENROUTER_KEY_HERE",
        "XAI_API_KEY": "YOUR_XAI_KEY_HERE",
        "AZURE_OPENAI_API_KEY": "YOUR_AZURE_KEY_HERE",
        "OLLAMA_API_KEY": "YOUR_OLLAMA_API_KEY_HERE"
      }
    }
  }
}

🔑 Replace YOUR_…_KEY_HERE with your real API keys. You can remove keys you don't use.

Note: If you see 0 tools enabled in the MCP settings, restart your editor and check that your API keys are correctly configured.

VS Code (servers + type)
{
  "servers": {
    "task-master-ai": {
      "command": "npx",
      "args": ["-y", "task-master-ai"],
      "env": {
        // "TASK_MASTER_TOOLS": "all", // Options: "all", "standard", "core", or comma-separated list of tools
        "ANTHROPIC_API_KEY": "YOUR_ANTHROPIC_API_KEY_HERE",
        "PERPLEXITY_API_KEY": "YOUR_PERPLEXITY_API_KEY_HERE",
        "OPENAI_API_KEY": "YOUR_OPENAI_KEY_HERE",
        "GOOGLE_API_KEY": "YOUR_GOOGLE_KEY_HERE",
        "MISTRAL_API_KEY": "YOUR_MISTRAL_KEY_HERE",
        "GROQ_API_KEY": "YOUR_GROQ_KEY_HERE",
        "OPENROUTER_API_KEY": "YOUR_OPENROUTER_KEY_HERE",
        "XAI_API_KEY": "YOUR_XAI_KEY_HERE",
        "AZURE_OPENAI_API_KEY": "YOUR_AZURE_KEY_HERE",
        "OLLAMA_API_KEY": "YOUR_OLLAMA_API_KEY_HERE"
      },
      "type": "stdio"
    }
  }
}

🔑 Replace YOUR_…_KEY_HERE with your real API keys. You can remove keys you don't use.

2. (Cursor-only) Enable Taskmaster MCP

Open Cursor Settings (Ctrl+Shift+J) ➡ Click on MCP tab on the left ➡ Enable task-master-ai with the toggle

3. (Optional) Configure the models you want to use

In your editor's AI chat pane, say:

Change the main, research and fallback models to <model_name>, <model_name> and <model_name> respectively.

For example, to use Claude Code (no API key required):

Change the main model to claude-code/sonnet

Table of available models | Claude Code setup

4. Initialize Task Master

In your editor's AI chat pane, say:

Initialize taskmaster-ai in my project

5. Make sure you have a PRD (Recommended)

For new projects: Create your PRD at .taskmaster/docs/prd.txt. For existing projects: You can use scripts/prd.txt or migrate with task-master migrate

An example PRD template is available after initialization in .taskmaster/templates/example_prd.txt.

[!NOTE] While a PRD is recommended for complex projects, you can always create individual tasks by asking "Can you help me implement [description of what you want to do]?" in chat.

Always start with a detailed PRD.

The more detailed your PRD, the better the generated tasks will be.

6. Common Commands

Use your AI assistant to:

  • Parse requirements: Can you parse my PRD at scripts/prd.txt?
  • Plan next step: What's the next task I should work on?
  • Implement a task: Can you help me implement task 3?
  • View multiple tasks: Can you show me tasks 1, 3, and 5?
  • Expand a task: Can you help me expand task 4?
  • Research fresh information: Research the latest best practices for implementing JWT authentication with Node.js
  • Research with context: Research React Query v5 migration strategies for our current API implementation in src/api.js

More examples on how to use Task Master in chat

Option 2: Using Command Line

Installation

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

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

Initialize a new project

# If installed globally
task-master init

# If installed locally
npx task-master init

# Initialize project with specific rules
task-master init --rules cursor,windsurf,vscode

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

# Show specific task(s) - supports comma-separated IDs
task-master show 1,3,5

# Research fresh information with project context
task-master research "What are the latest best practices for JWT authentication?"

# Move tasks between tags (cross-tag movement)
task-master move --from=5 --from-tag=backlog --to-tag=in-progress
task-master move --from=5,6,7 --from-tag=backlog --to-tag=done --with-dependencies
task-master move --from=5 --from-tag=backlog --to-tag=in-progress --ignore-dependencies

# Add rules after initialization
task-master rules add windsurf,roo,vscode

Tool Loading Configuration

Optimizing MCP Tool Loading

Task Master's MCP server supports selective tool loading to reduce context window usage. By default, all 36 tools are loaded (~21,000 tokens) to maintain backward compatibility with existing installations.

You can optimize performance by configuring the TASK_MASTER_TOOLS environment variable:

Available Modes

| Mode | Tools | Context Usage | Use Case | |------|-------|--------------|----------| | all (default) | 36 | ~21,000 tokens | Complete feature set - all tools available | | standard | 15 | ~10,000 tokens | Common task management operations | | core (or lean) | 7 | ~5,000 tokens | Essential daily development workflow | | custom | Variable | Variable | Comma-separated list of specific tools |

Configuration Methods

Method 1: Environment Variable in MCP Configuration

Add TASK_MASTER_TOOLS to your MCP configuration file's env section:

{
  "mcpServers": {  // or "servers" for VS Code
    "task-master-ai": {
      "command": "npx",
      "args": ["-y", "task-master-ai"],
      "env": {
        "TASK_MASTER_TOOLS": "standard",  // Options: "all", "standard", "core", "lean", or comma-separated list
        "ANTHROPIC_API_KEY": "your-key-here",
        // ... other API keys
      }
    }
  }
}

Method 2: Claude Code CLI (One-Time Setup)

For Claude Code users, you can set the mode during installation:

# Core mode example (~70% token reduction)
claude mcp add task-master-ai --scope user \
  --env TASK_MASTER_TOOLS="core" \
  -- npx -y task-master-ai@latest

# Custom tools example
claude mcp add task-master-ai --scope user \
  --env TASK_MASTER_TOOLS="get_tasks,next_task,set_task_status" \
  -- npx -y task-master-ai@latest

Tool Sets Details

Core Tools (7): get_tasks, next_task, get_task, set_task_status, update_subtask, parse_prd, expand_task

Standard Tools (15): All core tools plus initialize_project, analyze_project_complexity, expand_all, add_subtask, remove_task, generate, add_task, complexity_report

All Tools (36): Complete set including project setup, task management, analysis, dependencies, tags, research, and more

Recommendations

  • New users: Start with "standard" mode for a good balance
  • Large projects: Use "core" mode to minimize token usage
  • Complex workflows: Use "all" mode or custom selection
  • Backward compatibility: If not specified, defaults to "all" mode

Claude Code Support

Task Master now supports Claude models through the Claude Code CLI, which requires no API key:

  • Models: claude-code/opus and claude-code/sonnet
  • Requirements: Claude Code CLI installed
  • Benefits: No API key needed, uses your local Claude instance

Learn more about Claude Code setup

Troubleshooting

If task-master init doesn't respond

Try running it with Node directly:

node node_modules/claude-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

Join Our Team

Join Hamster's founding team

Contributors

Task Master project contributors

Star History

Star History Chart

Licensing

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

✅ Allowed:

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

❌ Not Allowed:

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

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

help

运行方式说明

cloud

托管运行

托管运行通常表示这个 MCP Server 由服务方环境承载，用户一般按页面提供的连接方式或授权流程接入，不需要在本地长期启动一个 MCP 进程

  1. 打开服务方连接页
  2. 完成授权或复制端点
  3. 在 MCP 客户端中连接
terminal

本地运行 / 其它方式

本地运行通常需要用户在自己的电脑或服务器上安装依赖，把 server_config 复制到 MCP 客户端，并按 env_schema 补齐环境变量、密钥或其它配置

  1. 复制 server_config
  2. 安装所需依赖
  3. 补齐环境变量后重启客户端