Todoist MCP Server

Todoist MCP Server

Enables AI assistants to manage Todoist tasks, projects, labels, sections, and comments through natural conversation. Supports comprehensive task operations including creation, updates, completion, and organization with natural language quick-add functionality.

Category
Visit Server

README

Todoist MCP Server

A comprehensive Model Context Protocol (MCP) server for Todoist that enables AI assistants to manage tasks, projects, labels, sections, and comments through natural conversation.

Features

The Todoist MCP server provides full task management capabilities:

📁 Project Management

  • List Projects - View all projects with hierarchy, colors, and metadata
  • Create Projects - Add new projects with customization options
  • Update Projects - Modify project properties like name, color, and view style

✅ Task Operations

  • List Tasks - View tasks with filters (by project, label, or Todoist filters)
  • Create Tasks - Add tasks with full control over properties
  • Quick Add Tasks - Use natural language to create tasks
  • Update Tasks - Modify task content, due dates, priorities, and labels
  • Complete Tasks - Mark tasks as done (handles recurring tasks automatically)

📑 Organization

  • Sections - List and create sections to organize tasks within projects
  • Labels - Manage personal labels for task categorization
  • Comments - Add and view comments on tasks and projects

Installation

Prerequisites

  • Python 3.9 or higher
  • A Todoist account with API access
  • Your Todoist API token (found in Settings → Integrations → Developer)

Setup

  1. Install the MCP Python SDK and dependencies:
pip install mcp httpx pydantic
  1. Save the server file:

Save todoist_mcp.py to a location on your system (e.g., ~/mcp-servers/todoist/)

  1. Make it executable:
chmod +x todoist_mcp.py

Configuration

For Claude Desktop

Add the following to your Claude Desktop configuration file:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json Windows: %APPDATA%\Claude\claude_desktop_config.json

{
  "mcpServers": {
    "todoist": {
      "command": "python",
      "args": ["/path/to/todoist_mcp.py"],
      "env": {
        "TODOIST_API_TOKEN": "your_api_token_here"
      }
    }
  }
}

Replace:

  • /path/to/todoist_mcp.py with the actual path to your server file
  • your_api_token_here with your Todoist API token

Getting Your Todoist API Token

  1. Log in to Todoist
  2. Go to Settings → Integrations → Developer
  3. Copy your API token
  4. Keep it secure - this token provides full access to your Todoist account

Usage Examples

Once configured, you can interact with Todoist through natural language:

Project Management

  • "Show me all my Todoist projects"
  • "Create a new project called 'Q1 Goals' with red color"
  • "Make my Work project a favorite"
  • "Change my Personal project to board view"

Task Management

  • "What tasks do I have due today?"
  • "Create a task 'Review quarterly report' in my Work project due tomorrow with high priority"
  • "Add task 'Call dentist next Monday at 2pm #Health p2'" (uses Quick Add)
  • "Mark task 123456 as complete"
  • "Update my 'Buy milk' task to be due tomorrow"
  • "Show me all tasks with the label 'urgent'"
  • "List tasks in my Work project"

Organization

  • "Create a section called 'In Progress' in my Work project"
  • "Show me all my labels"
  • "Create a new label called 'waiting' with blue color"
  • "Add a comment 'Started working on this' to task 789012"

Natural Language Quick Add

The Quick Add feature understands:

  • Projects: @ProjectName or #ProjectName
  • Labels: @LabelName
  • Priority: p1, p2, p3, p4 or !, !!, !!!
  • Due dates: today, tomorrow, next Monday, Jan 15, etc.

Examples:

  • "Meeting tomorrow at 3pm #Work p2"
  • "Buy groceries today @Shopping"
  • "Review document every Friday #Work"

Available Tools

Tool Description
todoist_list_projects List all projects with hierarchy and metadata
todoist_create_project Create a new project
todoist_update_project Update project properties
todoist_list_tasks List tasks with optional filters
todoist_create_task Create a task with full control
todoist_quick_add_task Add task using natural language
todoist_update_task Update task properties
todoist_complete_task Mark task as complete
todoist_list_sections List project sections
todoist_create_section Create a new section
todoist_list_labels List personal labels
todoist_create_label Create a new label
todoist_get_comments Get comments for task/project
todoist_add_comment Add a comment

Response Formats

Most tools support two response formats:

  • Markdown (default): Human-readable formatted text with emojis and structure
  • JSON: Machine-readable format with complete data

The server automatically uses the appropriate format based on context.

Rate Limits

Todoist API has the following limits:

  • Maximum 1000 requests per 15 minutes per user
  • 1 MB maximum request body size
  • 15 second processing timeout per request

The server provides clear error messages when limits are exceeded.

Error Handling

The server provides clear, actionable error messages:

  • Invalid API token errors with setup guidance
  • Rate limit notifications with wait recommendations
  • Resource not found errors with ID verification hints
  • Network timeout handling with retry suggestions

Security Notes

  • Store your API token securely - never commit it to version control
  • The API token provides full access to your Todoist account
  • Use environment variables for token storage
  • Consider using a separate Todoist account for testing

Troubleshooting

Common Issues

  1. "Invalid API token" error:

    • Verify your token in Todoist Settings → Integrations → Developer
    • Ensure the token is correctly set in the configuration
  2. "Resource not found" errors:

    • Check that project/task IDs are correct
    • IDs are now strings in Todoist API v2
  3. Rate limit errors:

    • Wait 15 minutes before making more requests
    • Consider batching operations where possible
  4. Connection timeouts:

    • Check your internet connection
    • Todoist API may be temporarily unavailable

Debug Mode

To see detailed error messages, run the server directly:

TODOIST_API_TOKEN=your_token python todoist_mcp.py

Development

Adding New Features

The server is built with FastMCP and follows MCP best practices:

  • Pydantic models for input validation
  • Comprehensive error handling
  • Support for both Markdown and JSON responses
  • Character limit handling for large responses

Code Structure

  • Pydantic Models: Input validation for all operations
  • Utility Functions: Shared API requests, error handling, formatting
  • Tool Definitions: Each tool with comprehensive docstrings
  • Response Formatting: Markdown and JSON output options

License

MIT License - See LICENSE file for details

Support

For issues or questions:

  1. Check the Todoist API documentation: https://developer.todoist.com/rest/v2/
  2. Review MCP documentation: https://modelcontextprotocol.io/
  3. File an issue on the project repository

Changelog

Version 1.0.0 (Initial Release)

  • Complete project management (list, create, update)
  • Full task operations (CRUD, complete, quick add)
  • Section and label management
  • Comment system support
  • Natural language task creation
  • Comprehensive error handling
  • Support for all Todoist filters
  • Markdown and JSON response formats

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured