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Task Planner MCP Server: Chaos Control & Workflow Precision - MCP Implementation

Task Planner MCP Server: Chaos Control & Workflow Precision

Task Planner MCP Server: The secret weapon for AI assistants like Claude to slice through chaos, track progress, and master complex workflows with step-by-step precision.

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73% of users reported increased productivity after just one week

About Task Planner MCP Server

What is Task Planner MCP Server: Chaos Control & Workflow Precision?

Task Planner MCP Server is a game-changing tool designed to tame chaos in complex workflows. Built on the Model Context Protocol (MCP), it acts as a smart task manager for AI assistants like Claude, breaking down overwhelming tasks into actionable steps. Think of it as your digital project director—automatically organizing tasks hierarchically, tracking progress in real-time, and ensuring nothing slips through the cracks. Whether planning a vacation or managing a software project, this server transforms confusion into clarity.

How to use Task Planner MCP Server: Chaos Control & Workflow Precision?

Getting started is straightforward:

  1. Install: Clone the repo, install dependencies, and build the project (code steps available in docs).
  2. Integrate with Claude: Configure your claude_desktop_config.json to point to the server.
  3. Start managing: Use natural language commands like "Break down project tasks" or "Mark step 3 as completed" to interact with the system.

Pro tip: Keep the server running as a background service for seamless AI collaboration.

Task Planner MCP Server Features

Key Features of Task Planner MCP Server: Chaos Control & Workflow Precision?

  • Hierarchical Task Mastery: Create parent tasks with unlimited subtasks, each with priority levels.
  • Progress Visualization: Instant status updates show exactly where tasks are in the "To Do/Doing/Done" spectrum.
  • AI Context Sync: Maintains perfect task history for Claude, eliminating the need for repeated explanations.
  • Priority Engine: Automatically highlights critical tasks while allowing manual override for custom workflows.

These features don't just organize tasks—they redefine how teams work together efficiently.

Use cases of Task Planner MCP Server: Chaos Control & Workflow Precision?

Perfect for scenarios where precision matters most:

Startup Launch Prep

Break down 50+ tasks into marketing, legal, and operations subcategories. Watch deadlines auto-highlight as launch day approaches.

Academic Research

Track literature reviews, experiment phases, and manuscript drafts with version-controlled task notes.

Personal Productivity

Automate daily routines while handling unexpected tasks with adaptive priority adjustments.

Task Planner MCP Server FAQ

FAQ from Task Planner MCP Server: Chaos Control & Workflow Precision?

Where are tasks stored?

In a secure local JSON file—no cloud required. Perfect for sensitive projects.

Does it work with other AI assistants?

Currently optimized for Claude, but the open API allows integration with any MCP-compatible assistant.

Can I export task data?

Yes! Export to CSV or JSON formats for audits or migration to other systems.

What happens if the server crashes?

Automatic backups occur every 15 minutes—no data loss in normal operating conditions.

Content

Task Planner MCP Server

An MCP (Model Context Protocol) server that helps AI assistants (like Claude) break down complex tasks into manageable steps, track progress, and manage a hierarchical task list.

Features

  • Create, update, and delete tasks
  • Break down complex tasks into multiple subtasks
  • Mark tasks as complete
  • View detailed task information
  • List all tasks or subtasks of a specific task
  • Set task priorities (low, medium, high)

Installation

# Clone the repository
git clone https://github.com/yourusername/task-planner-mcp.git
cd task-planner-mcp

# Install dependencies
pnpm install

# Build the project
pnpm run build

Usage

Running the server

pnpm start

Claude Desktop Configuration

To use this MCP server with Claude Desktop, add the following to your claude_desktop_config.json file:

{
  "mcpServers": {
    "task-planner": {
      "command": "node",
      "args": ["/absolute/path/to/task-planner-mcp/dist/index.js"]
    }
  }
}

Replace /absolute/path/to/task-planner-mcp with the absolute path to your task planner directory.

Available Tools

The Task Planner MCP Server provides the following tools:

create-task

Create a new task or subtask.

Parameters:

  • title: Title of the task
  • description (optional): Detailed description of the task
  • parentId (optional): ID of the parent task if this is a subtask
  • priority (optional): Priority level of the task (low, medium, high)

list-tasks

List all tasks or subtasks.

Parameters:

  • parentId (optional): ID of the parent task to list subtasks for

get-task

Get detailed information about a task.

Parameters:

  • id: ID of the task to retrieve

complete-task

Mark a task as completed.

Parameters:

  • id: ID of the task to complete

update-task

Update a task's details.

Parameters:

  • id: ID of the task to update
  • title (optional): New title for the task
  • description (optional): New description for the task
  • priority (optional): New priority level for the task (low, medium, high)

delete-task

Delete a task and its subtasks.

Parameters:

  • id: ID of the task to delete

break-down-task

Break down a complex task into multiple subtasks.

Parameters:

  • parentId: ID of the parent task to break down
  • subtasks: Array of subtask objects, each with:
    • title: Title of the subtask
    • description (optional): Description of the subtask
    • priority (optional): Priority of the subtask (low, medium, high)

Examples

Here are some examples of how to use the Task Planner with Claude:

  1. "Create a new task called 'Plan my vacation'"
  2. "Break down my vacation planning task into smaller steps"
  3. "What tasks do I have pending?"
  4. "Show me the details of my vacation planning task"
  5. "Mark the flight booking subtask as complete"
  6. "Delete the task about grocery shopping"

Data Storage

Task data is stored in a local JSON file (tasks.json) in the root directory of the project.

License

ISC

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