taskMaster-todoist

TaskMaster-Todoist MCP exposes a Todoist integration for Cursor AI, enabling you to query and manage Todoist tasks from within your coding environment. The server provides an MCP tool named get_tasks_tool which accepts a Todoist filter string and an optional priority to return tasks that match complex queries. You can filter by due dates (today, tomorrow, overdue), priorities (1-4, with 1 as highest), and a variety of date/band queries. The formatted task data includes priority, due date, and other relevant information with clear icons to help Cursor AI present tasks contextually. To use it, run the MCP server in your environment and configure Cursor AI to point at the server using your MCP.json configuration so Cursor can request task data and, in future plans, create or update tasks.

Prerequisites:

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

Install and run locally:

# 1) Clone the repository
git clone https://github.com/mingolladaniele/todoist-mcp.git
cd todoist-mcp

# 2) Install dependencies
pip install -r requirements.txt

Configure your Todoist API token as an environment variable:

# Linux/macOS
export TODOIST_API_TOKEN="your-api-token-here"

# Windows (PowerShell)
$env:TODOIST_API_TOKEN = "your-api-token-here"

Run the MCP server:

python server.py

Then point Cursor AI to the MCP server using the appropriate configuration file (for example, the default Cursor MCP config path) and ensure the server is reachable. You can customize the Todoist token and any other environment variables in your environment or in the Cursor MCP config as needed.

• The API token should be kept secret; do not commit it to version control.
• If you encounter authentication errors, double-check your Todoist API token in Todoist settings → Integrations → Developer.
• If the server cannot be reached by Cursor AI, verify network accessibility and that the server is running (green status in Cursor).
• The current MCP tool set focuses on retrieving tasks; future updates may add task creation, updates, and deletions.
• Ensure your Python virtual environment (if used) has access to the installed dependencies listed in requirements.txt.