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🚀 TaskMaster: Todoist MCP for Cursor AI

🚀 TaskMaster: Todoist MCP for Cursor AI

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github.com/mingolladanieleProductivity42Updated 67w ago

About 🚀 TaskMaster: Todoist MCP for Cursor AI

TaskMaster is an MCP server for Cursor AI that lets AI assistants read and filter Todoist tasks from the coding environment. It is designed to be lightweight and easy to maintain.

Key features

  1. 01Todoist filter syntax for task queries
  2. 02Filtering by due date and priority
  3. 03Formatted task output with priority and due date
  4. 04Integration with Cursor AI

Use cases

  1. 01Reviewing today's or overdue tasks from the IDE
  2. 02Listing high-priority to-dos while coding
  3. 03Checking upcoming deadlines during development

MCP support

This project is an MCP server that provides the get_tasks_tool task query tool to Cursor AI.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
"mcpServers": {
"taskMaster-todoist": {
"command": "npx",
"args": [
"-y",
"@smithery/cli"
]
}
}
}
Run commandnpx -y @smithery/cli

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
npm@smithery/cli

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

MseeP.ai Security Assessment Badge

🚀 TaskMaster: Todoist MCP for Cursor AI

smithery badge

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

Installing via Smithery

To install TaskMaster for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @mingolladaniele/taskMaster-todoist-mcp --client claude
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

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.