TaskPeace vs Task Master AI — for AI agents
Both are MCP-native task managers for AI agents, but different halves. Task Master AI parses a PRD into tasks inside one repo, stored locally in .taskmaster/. TaskPeace is a hosted cross-project priority queue — one global order, multi-agent leasing, a live board. Here's the honest comparison.
What is Task Master AI good at?
Task Master (claude-task-master, the task-master-ai package) is probably the best-known "task management for AI-driven development" tool. Its core move is PRD decomposition: you drop a requirements doc at .taskmaster/docs/prd.txt, run parse-prd, and it turns the spec into a dependency-ordered task list — then expands complex tasks into subtasks and can run research with project context. It ships both a CLI and an MCP server (the recommended path) that plugs into Cursor, Windsurf, VS Code, Claude Code, Roo and others. Everything lives as files in your repo, it's free with your own model API keys (Anthropic, OpenAI, Google, Perplexity and more), and it recently became part of the Hamster platform with an optional connected mode. For turning one repo's spec into an executable plan, it's excellent — and TaskPeace isn't trying to replace that.
Where does Task Master fall short for cross-project agent work?
Task Master is scoped to one repo at a time. Each project carries its own .taskmaster/ plan, so there's no single deterministic answer to "what's the next most important thing across everything I own?" It has no task leasing, so two parallel agent sessions sharing a plan can grab the same work; coordination between independent sessions isn't its job. And its state travels with the repo via git rather than living on a hosted board you can watch from anywhere, from any tool. It plans within a project; it isn't the queue above all your agents.
How do Task Master AI and TaskPeace compare for agent work?
| Capability | TaskPeace | Task Master AI |
|---|---|---|
| MCP-native | Yes (get_next_task pull) | Yes (MCP server + CLI) |
| PRD → task decomposition | Basic | Strong (parse-prd, expand, research) |
| One global priority order across projects | Yes | Per-repo .taskmaster/ plans |
| Multi-agent task leasing | Yes | No |
| Required results on completion | Yes | Status updates in task files |
| Hosted board / live cockpit | Yes | CLI + editor (optional Hamster platform) |
| Persists across sessions + machines | Yes (hosted) | Repo files (travel via git) |
| Open source | MIT · app source public · hosted service | MIT with Commons Clause · self-run, BYO API keys |
| Price | Free · $10/mo Pro | Free (your own model API keys) |
When is Task Master AI the better choice?
One repo, a real spec, and the value you're after is decomposition: parse the PRD, expand the tasks, execute in dependency order inside your editor — fully local, your own keys. Reach for TaskPeace when work spans several projects, multiple agent sessions need to share one queue safely, and you want a hosted cockpit with a durable results log. If you're running agents unattended, see the guide on running Claude Code autonomously.
Can I use Task Master AI and TaskPeace together?
Yes — it's a natural stack, because they operate at different layers. Use Task Master to decompose a PRD into an ordered plan inside a repo; put the milestones on the TaskPeace board so they compete for priority with everything else you own. Your agents then pull from one global queue — get_next_task returns the top task with merged project context, leasing keeps parallel sessions apart, and every complete_task requires a written result. See how the MCP queue works → or read the docs.
FAQ
What is Task Master AI?
Task Master AI (claude-task-master) is a popular open-source task-management system for AI-driven development. You give it a PRD and it parses it into a dependency-ordered task list, expands complex tasks into subtasks, and tracks them — via a CLI and an MCP server that plugs into Cursor, Windsurf, VS Code, Claude Code and other editors. Tasks live as files in a .taskmaster/ folder inside your repo, and you bring your own model API keys.
How is TaskPeace different from Task Master AI?
Both are MCP-native, but they solve different halves. Task Master turns a spec into a plan inside one repo. TaskPeace is a hosted queue with ONE global priority order across all your projects: agents call get_next_task and receive the top task with merged project context, task leasing stops parallel sessions colliding, every completion requires a written result, and a live board shows it all — persistent across sessions, machines and tools.
What do Task Master AI and TaskPeace cost?
Task Master is free to use (MIT with Commons Clause license) — you supply your own AI-model API keys, and there's an optional connected mode via the Hamster platform. TaskPeace has a free tier (150 active tasks, 3 projects, 50 agent completions per day) and a flat $10/mo Pro plan for unlimited use; its app source is open (MIT) too.
Can I use Task Master AI and TaskPeace together?
Yes — it's a natural stack. Use Task Master to decompose a PRD into an ordered plan inside a repo, and TaskPeace as the cross-project queue your agents actually pull from: the milestones go on the TaskPeace board, agents lease them one at a time, and results land back on the board.