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Claude Task Master

by eyaltoledano

Parses PRDs into structured tasks, expands implementation steps, and manages AI development work across multiple model providers.

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Install Claude Task Master

Pick your client, then add it in one click or paste the config.

STDIONode.js
~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "eyaltoledano-claude-task-master": {
      "command": "npx",
      "args": [
        "-y",
        "task-master-ai"
      ],
      "env": {
        "ANTHROPIC_API_KEY": "YOUR_VALUE_HERE",
        "OPENAI_API_KEY": "YOUR_VALUE_HERE",
        "GOOGLE_API_KEY": "YOUR_VALUE_HERE",
        "PERPLEXITY_API_KEY": "YOUR_VALUE_HERE",
        "XAI_API_KEY": "YOUR_VALUE_HERE",
        "OPENROUTER_API_KEY": "YOUR_VALUE_HERE",
        "MISTRAL_API_KEY": "YOUR_VALUE_HERE",
        "TASK_MASTER_TOOLS": "YOUR_VALUE_HERE"
      }
    }
  }
}

Settings → Developer → Edit Config, merge this into mcpServers, then fully quit and reopen Claude Desktop.

Values are written into the snippet above so you can paste it as is. They never leave your browser.

We couldn’t confirm it starts correctly

We ran the install command but it didn't respond within our test window — this can mean a slow first-time install rather than a real problem.

npx -y task-master-ai

No response to initialize.

This is an experimental automated check and can have false negatives — missing environment variables, a slow cold install, etc. It doesn’t necessarily mean something’s wrong. Last checked 1mo ago.

Overview

eyaltoledano/claude-task-master MCP server turns product requirements into structured development tasks for use from an AI-enabled editor. It runs locally through the `task-master-ai` npm package and exposes MCP capabilities for PRD parsing, task expansion, dependencies, research, and workflow management. Multiple AI providers can supply the main, research, and fallback models, with selective tool loading available to reduce context usage. Reach for it when an agent needs a persistent, structured way to plan and track implementation work from a PRD.

Use cases

  • Parse a PRD into an actionable task list
  • Expand high-level tasks into implementation steps
  • Track dependencies across development tasks
  • Organize work by tags and workstreams
  • Run research during AI-assisted planning

Key features

  • PRD parsing
  • Task expansion
  • Task dependencies
  • Tags and workstreams
  • Multi-provider model support
  • Selective MCP tool loading

Security & health

What it can reach and how reliably it runs — from our own checks, not the maintainer’s claims.

ActiveLast checked Today

Recent health check succeeded.

96/96 checks healthy over the last 60d

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 7d ago via OSV.dev · task-master-ai (npm)

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars28kStargazers on the source repository.
npm downloads68kPackage downloads in the last 30 days.
Last commit6mo agoMost recent push to the default branch.
Install checkInconclusiveDidn't respond in our test window — often a slow first install.
Directory activity11 viewsConfig copies, upvotes, and views on AllMCPs.

How Claude Task Master works

What eyaltoledano/claude-task-master MCP server does

eyaltoledano/claude-task-master MCP server provides task planning and management for AI-assisted software development. Its workflow starts with a product requirements document (PRD), which can be parsed into tasks and then expanded into more detailed implementation steps. Tasks support dependencies, tags, and workstreams, giving an AI client more structure than an untracked list of prompts.

The project is designed for use through MCP-compatible development environments. The README specifically documents Cursor, Windsurf, VS Code, and Q Developer CLI configuration, and describes the system as working with Claude and Cursor. It also includes CLI commands alongside its MCP interface.

How it works

The server runs as a local standard-input/standard-output process using the task-master-ai npm package. An MCP client starts it with npx -y task-master-ai, then communicates with the process using the client’s MCP configuration. The server uses configured AI models for operations such as task generation, task expansion, and research.

Three model roles are supported: a main model, a research model, and a fallback model. The research model is optional. Provider selection can include Anthropic, OpenAI, Google Gemini, Perplexity, xAI, OpenRouter, and other providers shown in the configuration example. Claude Code and Codex CLI are also listed as alternatives to directly supplying an API key, with Codex CLI using OAuth through a ChatGPT subscription.

Setup and configuration

Install the package through npm and register it in the MCP client configuration. Cursor and Windsurf use an mcpServers object, while VS Code uses a servers object and includes a server type in its configuration format. The README gives separate configuration locations for global and project-level setups.

At least one supported provider credential is needed for the AI-backed commands unless Claude Code or Codex CLI is being used. Keys can be placed in the project’s root .env file or in the MCP configuration’s env section. The one-click Cursor setup uses placeholder values, so those values must be replaced before use. If the client reports that no tools are enabled, the documented checks are to restart the editor and verify the API key configuration.

Tools and capabilities

eyaltoledano/claude-task-master MCP server supports capabilities documented around:

  • Parsing PRDs into tasks
  • Expanding tasks into implementation details
  • Managing task status and dependencies
  • Organizing work with tags and workstreams
  • Running research through a selected research model
  • Automating workflows with a loop command
  • Loading all, standard, core, or selected tools through TASK_MASTER_TOOLS

The available tool set can therefore be narrowed to a comma-separated selection instead of exposing every capability to the client.

Limitations and notes

The server does not remove the need for model-provider access. Most AI operations require at least one applicable API key, and using several providers requires configuring their respective keys. Research is optional, but it uses a separate research-model configuration when enabled.

The package is open source under an MIT license with a Commons Clause, as indicated by the repository badge; the Commons Clause may add restrictions beyond a standard MIT license.

Read the full README View source on GitHub

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Frequently Asked Questions about Claude Task Master

Run `npx -y task-master-ai` through your MCP client configuration, or use the documented Claude Code command `claude mcp add taskmaster-ai -- npx -y task-master-ai`.

At least one applicable provider key is required unless using Claude Code or Codex CLI.

Yes. The README provides a Cursor one-click installation link and manual `mcpServers` configuration for the package.

Set `TASK_MASTER_TOOLS` to `all`, `standard`, `core`, or a comma-separated list of tools in the MCP server environment.

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