The MCP TaskManager is a serverless task management system designed for AI assistants to handle complex multi-step workflows with built-in user approval mechanisms. With this server, you can:
Break down complex tasks into manageable sub-tasks using
request_planningTrack progress via
get_next_taskand progress tablesMark tasks as completed with
mark_task_doneRequire user approval for completed tasks and entire requests
Inspect task details and list all requests
Add, update, or delete tasks within existing requests
Persistently store task data using Cloudflare KV
Interact through a RESTful API compliant with the Model Context Protocol
Support cross-origin requests (CORS) for web integration
MCP TaskManager
Model Context Protocol server for Task Management. This allows Claude Desktop (or any MCP client) to manage and execute tasks in a queue-based system.
Quick Start (For Users)
Prerequisites
Node.js 18+ (install via
brew install node)Claude Desktop (install from https://claude.ai/desktop)
Configuration
Open your Claude Desktop configuration file at:
~/Library/Application Support/Claude/claude_desktop_config.json
You can find this through the Claude Desktop menu:
Open Claude Desktop
Click Claude on the Mac menu bar
Click "Settings"
Click "Developer"
Add the following to your configuration:
Related MCP server: MCP Memory Server
For Developers
Prerequisites
Node.js 18+ (install via
brew install node)Claude Desktop (install from https://claude.ai/desktop)
tsx (install via
npm install -g tsx)
Installation
Development Configuration
Make sure Claude Desktop is installed and running.
Install tsx globally if you haven't:
Modify your Claude Desktop config located at:
~/Library/Application Support/Claude/claude_desktop_config.json
Add the following to your MCP client's configuration:
Available Operations
The TaskManager supports two main phases of operation:
Planning Phase
Accepts a task list (array of strings) from the user
Stores tasks internally as a queue
Returns an execution plan (task overview, task ID, current queue status)
Execution Phase
Returns the next task from the queue when requested
Provides feedback mechanism for task completion
Removes completed tasks from the queue
Prepares the next task for execution
Parameters
action: "plan" | "execute" | "complete"tasks: Array of task strings (required for "plan" action)taskId: Task identifier (required for "complete" action)getNext: Boolean flag to request next task (for "execute" action)
Example Usage
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