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Claude Task Master

Claude Task Master

AI-driven task management and decomposition for long-running agent projects.

Score 86(?)Eyal Toledano (community)MIT27kVerified Top MCPs for Agent Orchestration →
InstallView on GitHub

Quick answer

What it does

Exposes tools to add, expand, complete, and reorder tasks. Stores state on disk so an agent can pick up exactly where it left off across sessions, models, and clients.

Best for

  • Multi-week coding projects
  • Plan-then-execute agent loops
  • Cross-session continuity
  • Decomposing vague specs into checklists

Not for

  • Single-session tasks
  • Team workflows that need collaboration features

Setup recipe

Pick your client, then follow the three steps.

  1. 1

    Install

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

    Paste under mcpServers. Fully quit and reopen Claude after editing.

    CLI or .mcp.json
    claude mcp add task-master-ai -- npx -y task-master-mcp

    Run from your repo. Commit .mcp.json to share with your team.

    .cursor/mcp.json
    {
  "mcpServers": {
    "task-master-ai": {
      "command": "npx",
      "args": [
        "-y",
        "task-master-mcp"
      ]
    }
  }
}

    Global path: ~/.cursor/mcp.json. Reload window after editing.

    .vscode/mcp.json
    {
  "servers": {
    "task-master-ai": {
      "command": "npx",
      "args": [
        "-y",
        "task-master-mcp"
      ]
    }
  }
}

    VS Code uses the "servers" key (not "mcpServers").

    ~/.codeium/windsurf/mcp_config.json
    {
  "mcpServers": {
    "task-master-ai": {
      "command": "npx",
      "args": [
        "-y",
        "task-master-mcp"
      ]
    }
  }
}

    Open via Cascade → hammer icon → Configure.

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

    Open via the Cline sidebar → MCP Servers → Edit.

    ~/.continue/config.json
    {
  "experimental": {
    "modelContextProtocolServers": [
      {
        "transport": {
          "type": "stdio",
          "command": "npx",
          "args": [
            "-y",
            "task-master-mcp"
          ]
        }
      }
    ]
  }
}

    Continue uses modelContextProtocolServers with a transport block.

    ~/.codex/config.toml
    # ~/.codex/config.toml
[mcp_servers.task-master-ai]
command = "npx"
args = [
  "-y",
  "task-master-mcp",
]

    Codex uses TOML. Each server is a [mcp_servers.<name>] subtable.

    ~/.config/zed/settings.json
    {
  "context_servers": {
    "task-master-ai": {
      "command": {
        "path": "npx",
        "args": [
          "-y",
          "task-master-mcp"
        ]
      }
    }
  }
}

    Zed calls them "context_servers". Settings live-reload on save.

    ChatGPT → Apps directory

    Claude Task Master doesn't ship a hosted HTTPS endpoint today. ChatGPT supports remote MCP servers only — to use this server in ChatGPT you'll need to deploy it to a public HTTPS URL first (e.g. via Cloudflare Workers or Vercel) or wait for an official remote build.

  2. 2

    Set required secrets

    No credentials required — this MCP runs over stdio without authentication.

  3. 3

    Try a minimum working prompt

    Minimum working prompt pending verification. Try any prompt from the MCP’s README once installed.

Tools & permissions

Tools list pending verification. The server exposes tools over MCP; we haven’t yet parsed its capability manifest into this page. Check the GitHub repo for the authoritative list.

Security & scope

Access scope
Read + write
Sandbox
Reads and writes to a `.taskmaster` directory inside the project root. No network calls.
Gotchas
  • State files are checked in by default — review before committing sensitive task descriptions.
  • Concurrent edits across multiple agents are not coordinated; one writer at a time.

Agent prompt pack

— copy into Claude, Cursor, or ChatGPT.
Paste into Claude, Cursor, or ChatGPT. Edit the [brackets] before sending.
Recommend the best MCP servers for [task: e.g. agent orchestration work] in [client: Claude].

Constraints:
- Prefer tools that are [official | open-source | read-only] — pick what matters for my use case.
- Exclude MCPs that require [e.g. a paid plan, OAuth-only flows, remote-only transport].
- Return at most 3 picks, ranked.

For each pick include:
1. One-sentence rationale.
2. The ready-to-paste install snippet for my client.
3. Any required secrets I need to create before installing.

Cross-check the top-mcps.com listing: https://top-mcps.com/top-mcps-for-agent-orchestration
Compare Claude Task Master against a real alternative. Swap the second MCP in [brackets] if you want a different match.
Compare Claude Task Master MCP vs [Sequential Thinking MCP] for the following job: [describe the job, e.g. "let an agent create GitHub issues on bug triage"].

Judge them on:
- Setup time and complexity (what a new user hits first).
- Auth model (none / API key / OAuth 2.1) and credential risk.
- Transport (stdio / Streamable HTTP / SSE) and where the server runs.
- Required secrets and the blast radius if they leak.
- Operational risk in an unattended agent loop.
- Which one is "good enough" for a weekend prototype vs. production.

End with one sentence: which should I pick for my scenario, which is: [my scenario].

References:
- https://top-mcps.com/mcp/task-master-ai
- top-mcps.com listing for Sequential Thinking
Asks the agent to install and verify. Works inside Claude Code, Cursor Agent, Codex CLI.
Install the Claude Task Master MCP server for my [client: Claude] at the default config path for that client.

Use the exact install snippet published at https://top-mcps.com/mcp/task-master-ai (fetch https://top-mcps.com/mcp/task-master-ai.json for the canonical server.json if you can read URLs).

Before finishing:
1. Create the required secrets (no secrets) and put them in the appropriate env block — do not hard-code them.
2. Restart or reload the client so it picks up the new server.
3. Verify the server is connected (green / running state) and at least one tool is listed.
4. If anything fails, read the client's MCP logs and report the exact error — do not silently retry.

Confirm when done and list the tools the server now exposes.

Frequently asked questions

What changed

— 2 updates tracked.

  1. Refreshed install snippets and fact sheet; verified for 2026.

  2. Initial directory listing.

More Agent Orchestration MCPs

Other tools in the same category worth evaluating.

Sequential Thinking

Structured step-by-step reasoning for complex problem solving.

reasoningthinkingagentsplanning
2 minLow
Memory

Persistent knowledge graph memory across AI conversations.

memorypersistenceknowledge-graphagents
2 minLow
Zen MCP

Multi-model orchestration — let Claude consult Gemini, GPT, and o-series as sub-agents.

agentorchestrationmulti-modelconsensus
10 minMedium

Compared with Claude Task Master

Side-by-side breakdowns for the choices people most often weigh against this MCP.

Claude Task MastervsSequential ThinkingClaude Task MastervsMemoryClaude Task MastervsZen MCPClaude Task MastervsContext Forge

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