MCP Todoist: AI Automation & Scalable Workflows

What is MCP Todoist: AI Automation & Scalable Workflows?

MCP Todoist is a Model Context Protocol (MCP) server designed to integrate the Claude AI platform with Todoist task management. This tool enables users to automate workflows, manage tasks at scale, and leverage AI-powered interactions with their Todoist account. By bridging Claude's cognitive capabilities with Todoist's organizational features, it streamlines task creation, filtering, and project management through natural language commands.

How to Use MCP Todoist: AI Automation & Scalable Workflows?

Implementation follows three core steps:

1. Installation: Use Astral UV to install the package via uvx mcp-todoist.
2. Configuration: Set your Todoist API token in environment variables and configure Claude Desktop's MCP server settings with the required JSON payload.
3. Interaction: Issue natural language commands in Claude Desktop, such as "Create a task for 'submit report' on Friday" or "List overdue tasks in my Work project".

For advanced users, startup scripts and debug configurations ensure robust server management.

Key Features of MCP Todoist: AI Automation & Scalable Workflows?

Core functionalities include:

• Task Automation: Full lifecycle management (create, update, complete/delete) with date/time parameters and context awareness.
• Structured Organization: Project and label management tools to categorize tasks hierarchically.
• Advanced Search: Contextual filtering using Todoist's API capabilities via the search tool.
• Seamless Integration: Native compatibility with Claude Desktop, reducing setup friction for AI-driven workflows.

Use Cases of MCP Todoist: AI Automation & Scalable Workflows?

Common applications include:

• Automating recurring tasks through scheduled Claude interactions.
• Generating dynamic task lists based on project deadlines or priority labels.
• Centralized workflow management for remote teams using shared Todoist projects.
• Error-resistant task updates via natural language parsing (e.g., "Mark delayed tasks as high priority").

FAQ from MCP Todoist: AI Automation & Scalable Workflows?

• Q: Why use MCP instead of Todoist's API directly?
  Gain AI-driven contextual understanding - e.g., Claude can infer task deadlines from natural language without explicit date formatting.
• Q: How do I troubleshoot server connectivity?
  Verify the MCP server process is running, check API token validity, and use the MCP Inspector tool for real-time debugging.
• Q: Can I customize workflows beyond built-in commands?
  Yes - extend functionality by modifying tools in the mcp_todoist/tools module or creating custom startup scripts.
• Q: What logging capabilities exist?
  Configure verbosity via MCP_DEBUG, and use startup scripts to persist logs for audit trails and error analysis.

Refer to the Astral UV documentation for dependency management and advanced deployment scenarios.

MCP Todoist

A Model Context Protocol (MCP) server that enables Claude to interact with your Todoist account.

Features

• Manage tasks: create, update, complete, and delete tasks
• Organize tasks in projects and with labels
• Search and filter tasks based on various criteria
• Seamless integration with Claude Desktop

Prerequisites

• Python 3.11+
• Astral UV
• Todoist account and API token
• Claude Desktop (for using the MCP server)

Quick Start

1. Installation

# Install using UV
uvx mcp-todoist

2. Configuration

1. Get your Todoist API token from Todoist Integrations settings

2. Configure the environment variable:

   Add to your .env file or environment

TODOIST_API_TOKEN=your_api_token_here

3. Configure Claude Desktop:

   // ~/.config/claude/claude_desktop_config.json or equivalent

{
  "mcpServers": {
    "mcp-todoist": {
      "command": "uvx",
      "args": ["mcp-todoist"]
    }
  }
}

3. Using with Claude

Once configured, you can ask Claude to interact with your Todoist account:

• "Show me my tasks due today"
• "Create a new task to buy groceries tomorrow"
• "Mark my 'send email' task as complete"
• "Create a new project called 'Home Renovation'"
• "Show me all tasks in my Work project"

Available Tools

Task Management

• list-tasks - Retrieve and filter tasks
• create-task - Create a new task
• update-task - Update an existing task
• complete-task - Mark a task as completed
• delete-task - Delete a task

Project Management

• list-projects - Get all projects
• create-project - Create a new project
• update-project - Update a project
• delete-project - Delete a project

Label Management

• list-labels - Get all labels
• create-label - Create a new label
• update-label - Update a label
• delete-label - Delete a label

Utilities

• search - Search across tasks with complex filtering

Running the MCP Server

There are multiple ways to run the Todoist MCP server:

Method 1: Direct Command Line

Run the server in a terminal window:

# Set your API token
export TODOIST_API_TOKEN=your_api_token_here

# Run the server using UV
uvx mcp-todoist

# Alternative: Run from source
cd /path/to/mcp-todoist
uv run python -m mcp_todoist

Keep this terminal window open while using Claude Desktop.

Method 2: Using a Startup Script (Recommended)

Create a startup script that Claude Desktop can use to automatically start the server:

1. Create a file named start-todoist-mcp.sh with the following content:

#!/bin/bash

# Set environment variables
export MCP_SERVER_NAME="mcp-todoist"
export MCP_LOG_LEVEL="INFO"
export MCP_DEBUG="true"
export TODOIST_API_TOKEN="your_todoist_api_token_here"

# Path to your Todoist MCP server
MCP_PATH="/path/to/mcp-todoist"

# Log file for debugging
LOG_FILE="${MCP_PATH}/todoist-mcp.log"

# Create log file or clear existing one
echo "Starting Todoist MCP server at $(date)" > "${LOG_FILE}"

# Navigate to the project directory
cd "${MCP_PATH}"

# Start the MCP server
echo "Starting MCP server from ${MCP_PATH}" >> "${LOG_FILE}"
uv run python -m mcp_todoist >> "${LOG_FILE}" 2>&1

2. Make the script executable:

chmod +x start-todoist-mcp.sh

3. Update your Claude Desktop configuration to use this script:

{
  "mcpServers": {
    "mcp-todoist": {
      "command": "/absolute/path/to/start-todoist-mcp.sh",
      "args": []
    }
  }
}

This approach offers several advantages:

• The server starts automatically with Claude Desktop
• All logs are captured in a file for easier debugging
• Environment variables are set consistently

Debugging

If you encounter issues with the MCP server, here are some debugging strategies:

1. Check the Logs

If using the startup script, check the log file:

cat /path/to/mcp-todoist/todoist-mcp.log

2. Enable Debug Mode

Set the MCP_DEBUG environment variable to true for more verbose logging:

export MCP_DEBUG=true
uvx mcp-todoist

3. Verify API Token

Ensure your Todoist API token is correct and still valid:

# Test the token with a simple curl request
curl -X GET \
  https://api.todoist.com/rest/v2/projects \
  -H "Authorization: Bearer $TODOIST_API_TOKEN"

4. Use the MCP Inspector

The MCP Inspector is a powerful tool for debugging MCP servers:

npx @modelcontextprotocol/inspector uvx mcp-todoist

This will open a web interface showing all communications between Claude and the MCP server.

5. Common Issues and Solutions

• "MCP Server not available" error : Ensure the server is running in a separate terminal or via a startup script.
• Authentication errors : Check that your Todoist API token is correctly set in your environment.
• "Command not found" errors : Make sure Astral UV is installed and in your PATH.
• Timeout errors : If your MCP server is slow to respond, try increasing the timeout in Claude Desktop settings.

Development

Setup

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

# Install dependencies
uv sync

Testing

# Run tests
uv run pytest

Local Development

For local development, you can create a .env file with your Todoist API token:

TODOIST_API_TOKEN=your_api_token_here

Then run the server:

uv run python -m mcp_todoist

License

MIT License - see LICENSE file for details.