Todoist MCP Server

Todoist MCP Server

An MCP server that integrates with the Todoist REST API v2 to enable AI assistants to manage tasks, projects, sections, comments, and labels. It supports comprehensive operations including batch task creation, history tracking for completed tasks, and organized project management.

Category
Visit Server

README

Todoist MCP Server

A Model Context Protocol (MCP) server that provides integration with the Todoist REST API v2, enabling AI assistants to manage tasks, projects, sections, comments, and labels.

Note: I used this project to test out Factory.ai -- use with caution.

Features

  • Task Management: Create, update, complete, delete, move, and search tasks
  • Batch Operations: Create multiple tasks at once
  • Project Management: Create, update, and delete projects
  • Section Management: Organize tasks within project sections
  • Comments: Add rich text comments with markdown support and optional prefixes ([Research], [Prompt], [Context], etc.)
  • Labels: Manage personal labels
  • Completed Tasks: Access completed task history via Sync API
  • Rate Limiting: Built-in handling for Todoist's 450 requests/15 min limit with exponential backoff

Installation

npm install
npm run build

Configuration

  1. Get your Todoist API token from Todoist Settings > Integrations > Developer

  2. Add to your MCP client configuration (e.g., Claude Desktop):

{
  "mcpServers": {
    "todoist": {
      "command": "node",
      "args": ["/path/to/todoist-mcp/dist/index.js"],
      "env": {
        "TODOIST_API_TOKEN": "your-api-token"
      }
    }
  }
}

Important: Never commit your API token to version control. Store it securely in your local MCP configuration.

Available Tools

Task Operations

  • todoist_list_tasks - List active tasks with filters
  • todoist_get_task - Get a single task
  • todoist_create_task - Create a new task
  • todoist_update_task - Update an existing task
  • todoist_complete_task - Mark task as completed
  • todoist_reopen_task - Reopen a completed task
  • todoist_delete_task - Delete a task
  • todoist_move_task - Move task to different project/section
  • todoist_search_tasks - Search tasks by content
  • todoist_create_tasks_batch - Create multiple tasks at once

Project Operations

  • todoist_list_projects - List all projects
  • todoist_get_project - Get a project
  • todoist_create_project - Create a new project
  • todoist_update_project - Update a project
  • todoist_delete_project - Delete a project

Section Operations

  • todoist_list_sections - List all sections
  • todoist_get_section - Get a section
  • todoist_create_section - Create a new section
  • todoist_update_section - Update a section
  • todoist_delete_section - Delete a section

Comment Operations

  • todoist_list_comments - List comments for task/project
  • todoist_get_comment - Get a comment
  • todoist_create_comment - Create a comment with optional prefix
  • todoist_update_comment - Update a comment
  • todoist_delete_comment - Delete a comment
  • todoist_add_research_comment - Add [Research] prefixed comment
  • todoist_add_context_comment - Add [Context] prefixed comment

Label Operations

  • todoist_list_labels - List all labels
  • todoist_create_label - Create a new label
  • todoist_update_label - Update a label
  • todoist_delete_label - Delete a label

Completed Tasks

  • todoist_list_completed_tasks - List completed tasks
  • todoist_get_completed_stats - Get completion statistics

Response Format

All tools return a structured response:

{
  success: boolean;
  data?: any;        // Present on success
  error?: {          // Present on failure
    code: string;
    message: string;
    details?: any;
  };
}

Development

npm run dev    # Watch mode for development
npm run build  # Build for production
npm run typecheck  # Type check without emitting

License

ISC

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
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
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
Qdrant Server

Qdrant Server

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

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
E2B

E2B

Using MCP to run code via e2b.

Official
Featured