Todo

Todo MCP Server

A Model Context Protocol (MCP) server that provides an autonomous task management system with support for both stdio and HTTP (Streamable) transports.

Features

• Random String Generation: Generates random 6-character alphanumeric strings
• Task Management: AI Agent can autonomously create, manage, and execute task lists with SQLite persistence
• Multiple Transport Modes:
  • Stdio Transport: Standard MCP communication via stdin/stdout
  • HTTP Transport: RESTful API with Server-Sent Events (SSE) support for real-time notifications
• MCP Standard Compliance: Fully compliant with MCP specifications

Usage

Stdio Transport (Default)

Claude Desktop

//use directly with npx
{
  "mcpServers": {
    "todo":{
      "command": "npx",
      "args": ["github:stilllovee/todo-mcp-server"]
    }
  }
}

//or use after clone repo
{
  "mcpServers": {
    "todo":{
      "command": "node",
      "args": ["PATH_TO_YOUR_FOLDER"]
    }
  }
}

Github Copilot

//use directly with npx
{
    "servers": {
        "todo": {
            "type": "stdio",
            "command": "npx",
            "args": ["github:stilllovee/todo-mcp-server"]
        },
    },
    "inputs": []
}

//or use after clone repo
{
    "servers": {
        "todo": {
            "type": "stdio",
            "command": "node",
            "args": ["PATH_TO_YOUR_FOLDER"]
        }
    },
    "inputs": []
}

The server runs on stdio transport and communicates via standard input/output.

Example instruction:

System prompt

From the input requirement, if it is a complex requirement then break it down into smaller tasks in a logical order and use the "add" tool to save each task to the list.

Then, repeat the following steps until all tasks are completed:

1. Call the "next" tool to get the next pending task. If there are no tasks left, exit the loop.

2. Execute the task by reasoning, planning, and automatically calling any necessary tools if appropriate, without asking for permission.

3. After finishing, go back to step 1.

User prompt

Build the backend for a mood journaling web application.

Requirements:

Design a database schema (SQLite or PostgreSQL).

Build a backend API using Node.js (Express) with endpoints:

Log mood entries

View mood logs

HTTP Transport (Streamable)

Start the HTTP server:

# Default port (8123)
npm run start:http

# Custom port
node http-server.js --port=3000

The server will be available at: http://localhost:8123/mcp

Github Copilot Configuration (HTTP)

{
    "servers": {
        "todo-http": {
            "type": "http",
            "url": "http://localhost:8123/mcp"
        }
    },
    "inputs": []
}

Available Tools

Task Management Tools

add

Add a new task to the current session's list.

next

Get the next task from the session.

Task Management System

The server includes an autonomous task management system that allows AI Agents to:

1. Create Task Lists: Generate comprehensive task lists from high-level requests
2. Manage Tasks: Add, and move to next tasks in a session
3. Session Isolation: Each session maintains its own separate task list
4. Persistent Storage: All tasks are stored in SQLite database for persistence