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todo-mcp-server

by idsulik·7·Score 32

A minimal Todo MCP server providing basic task management operations through Model Context Protocol.

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Overview

The todo-mcp-server is a Python implementation of a todo application as an MCP server, offering core functionality like listing, viewing, adding, removing, and clearing todo items. It provides both MCP resources and tools for todo management, with support for structured tasks including priority levels and due dates. The server can be installed via uv package manager, integrated with Claude Desktop, or run in Docker for easy deployment.

Try asking AI

After installing, here are 3 things you can ask your AI assistant:

you:Personal task management within AI assistants
you:Demonstration of MCP server implementation patterns
you:Integration with AI workflows for todo tracking

When to choose this

Choose this for personal task management within AI assistants or as a reference implementation for learning MCP server development.

When NOT to choose this

Don't choose this for team collaboration needs as it appears to be designed for single-user scenarios with no apparent multi-user support.

Tools this server exposes

4 tools extracted from the README
  • add_todoadd_todo(value: str)

    Add a new todo item to the todo list

  • remove_todoremove_todo(item_idx: int)

    Remove a specific todo item by its index

  • clear_todoclear_todo()

    Clear all todo items from the list

  • create_taskcreate_task(task_name: str, priority: str = "medium", due_date: str = "")

    Create a structured todo task with priority and due date

Comparable tools

mcp-todo-serverclaude-todoreminders-mcptodoist-api-mcpgoogle-tasks-mcp

Installation

Installation

  1. Clone the repository:
git clone https://github.com/idsulik/todo-mcp-server.git
cd todo-mcp-server
  1. Install dependencies using uv:
uv pip install -e .

Adding to Claude Desktop

Add this to your Claude Desktop configuration file:

{
  "mcpServers": {
    "todo": {
      "command": "uv",
      "args": [
        "run",
        "--with",
        "mcp[cli]",
        "mcp",
        "run",
        "/path/to/your/server.py"
      ]
    }
  }
}

Using Docker

Alternatively, you can use Docker:

{
  "mcpServers": {
    "todo": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "idsulik/todo-mcp-server"
      ]
    }
  }
}

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Last updated · Auto-generated from public README + GitHub signals.