Todoist MCP Server
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- AlicenseNot gradedqualityDmaintenanceEnables interaction with Todoist through the MCP interface, providing full CRUD operations for tasks and projects including creating, updating, completing, and filtering tasks with natural language commands.4 npmMIT
- AlicenseNot gradedqualityBmaintenanceEnables AI agents to create, read, and manage tasks and projects in a personal todo system through MCP tools.MIT

Todoist AI MCP Serverofficial
AlicenseAqualityAmaintenanceEnables AI agents to access and modify Todoist accounts to manage tasks and projects on the user's behalf. It provides a suite of tools for task operations and supports interactive UI widgets for a rich visual experience in AI chat interfaces.473,840 npm550MIT- AlicenseNot gradedqualityDmaintenanceEnables AI assistants to manage Todoist tasks, projects, comments, and labels through natural language commands. Provides complete CRUD operations securely via the Todoist REST API v2.Apache 2.0
- AlicenseAqualityDmaintenanceConnect AI agents to your Todoist tasks via the Model Context Protocol (MCP).281MIT
- AlicenseNot gradedqualityFmaintenanceEnables AI assistants to manage Todoist tasks, projects, sections, labels, and comments through natural language conversations, providing complete control over your productivity workflow via the Todoist API.144 npm7MIT
TDQS
Scored across 47 tools
The tool set covers a wide range of resources (tasks, projects, comments, labels, filters, reminders, etc.) with mostly distinct purposes. However, several tools overlap in retrieval of tasks (find-tasks, find-tasks-by-date, find-completed-tasks, search, fetch, fetch-object, get-overview) but detailed descriptions clarify when to use each, so agents can disambiguate with effort.
The majority of tools follow a consistent verb-noun pattern (add-, update-, find-, get-, list-, etc.). There are a few outliers like 'project-management', 'project-move', 'user-info', and 'search' that break the pattern, but they are still readable and predictable overall.
47 tools is excessive for a single server, even for a comprehensive task management API. While the scope covers many resources and features, the high count risks overwhelming agents and complicates tool selection. The calibration suggests 25+ is too many, and this is close to extreme.
The tool surface is very comprehensive, covering CRUD and lifecycle operations for tasks, projects, sections, comments, labels, filters, reminders, and more. It also includes health analysis, activity logs, template import/export, and workspace management. Minor gaps exist (e.g., no dedicated 'get task by ID' but fetch-object covers it) but overall the domain is well-covered.