mingolladaniele taskMaster todoist mcp

mingolladaniele taskMaster todoist mcp avatar

by mingolladaniele

A lightweight Model Context Protocol (MCP) server that enables natural language interaction with your Todoist tasks directly from your IDE. Built with simplicity and maintainability in mind.

What is mingolladaniele taskMaster todoist mcp

🚀 TaskMaster: Todoist MCP for Cursor AI

A Model Context Protocol (MCP) server implementation for Todoist integration, specifically developed for Cursor AI. This server allows Cursor AI assistants to interact with your Todoist tasks directly from your coding environment.

Demo Video

TaskMaster Demo

Features

  • Flexible Task Filtering: Filter tasks using Todoist's powerful filter syntax
    • Filter by due date: today, tomorrow, overdue
    • Filter by priority levels (1-4, where 1 is highest)
    • Filter using complex query combinations
  • Rich Task Formatting: Each task displays priority, due date, and other relevant information with clear icons
  • Cursor AI Integration: Seamlessly use Todoist within your Cursor AI coding environment

Installation

Prerequisites

  • Python 3.10 or higher
  • Poetry (for dependency management)
  • Todoist account and API token

Setup

  1. Clone this repository:
git clone https://github.com/mingolladaniele/todoist-mcp.git
cd todoist-mcp
  1. Install dependencies:
pip install -r requirements.txt
  1. Set your Todoist API token as an environment variable:
# Linux/macOS
export TODOIST_API_TOKEN="your-api-token-here"

# Windows
set TODOIST_API_TOKEN="your-api-token-here"

You can find your Todoist API token in Todoist settings → Integrations → Developer.

Usage

Running the server

python server.py

MCP Tool

The server provides the following MCP tool:

get_tasks_tool

Retrieves tasks with powerful filtering options.

Parameters:

  • filter_string: Advanced Todoist filter query string for complex filtering
  • priority: Optional priority level (1-4, where 1 is highest priority)

Example filter strings:

  • "today" - Tasks due today
  • "overdue" - Overdue tasks
  • "Jan 3" - Tasks due on January 3rd
  • "due before: May 5" - Tasks due before May 5th
  • "due after: May 5" - Tasks due after May 5th
  • "due before: +4 hours" - Tasks due within the next four hours and all overdue tasks
  • "no date" - Tasks with no due date
  • "5 days" or "next 5 days" - Tasks due in the next 5 days
  • "recurring" - Tasks with a recurring date

Setting up with Cursor AI

To use with Cursor AI, create or edit the MCP configuration file:

Windows: C:\Users\<username>\.cursor\mcp.json

{
  "mcpServers": {
    "todoist-mcp": {
      "command": "C:/Users/<username>/path/to/todoist-mcp/.venv/Scripts/python.exe",
      "args": [
        "C:/Users/<username>/path/to/todoist-mcp/server.py"
      ],
      "env": {
        "TODOIST_API_TOKEN": "your-api-token-here"
      }
    }
  }
}

Replace <username> and paths with your actual username and the correct paths to your installation.

Once you do that, go to Cursor Settings → MCP and check that the server is correctly running (green dot).

Project Structure

The codebase is organized into modules:

  • api/: API wrapper for Todoist
  • config/: Configuration and settings
  • utils/: Utility functions and helpers including task formatting

Roadmap

Here are the features planned for future releases:

  • Task Creation: Add new tasks to your Todoist directly from Cursor AI
  • Task Completion: Mark tasks as complete without switching context
  • Task Deletion: Remove tasks that are no longer needed
  • Smart Task Balancing: AI-powered task rebalancing based on:
    • Project priority
    • Time commitments
    • Due dates
    • Current workload
  • Project Management: Create and manage Todoist projects
  • Labels and Filters: Add custom labels and create saved filters

License

MIT License

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Frequently Asked Questions

What is MCP?

MCP (Model Context Protocol) is an open protocol that standardizes how applications provide context to LLMs. Think of MCP like a USB-C port for AI applications, providing a standardized way to connect AI models to different data sources and tools.

What are MCP Servers?

MCP Servers are lightweight programs that expose specific capabilities through the standardized Model Context Protocol. They act as bridges between LLMs like Claude and various data sources or services, allowing secure access to files, databases, APIs, and other resources.

How do MCP Servers work?

MCP Servers follow a client-server architecture where a host application (like Claude Desktop) connects to multiple servers. Each server provides specific functionality through standardized endpoints and protocols, enabling Claude to access data and perform actions through the standardized protocol.

Are MCP Servers secure?

Yes, MCP Servers are designed with security in mind. They run locally with explicit configuration and permissions, require user approval for actions, and include built-in security features to prevent unauthorized access and ensure data privacy.

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