Todoist MCP Server
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Alternatives to Todoist MCP Server
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- FlicenseNot gradedqualityCmaintenanceEnables Claude Desktop and other MCP clients to manage Todoist tasks, projects, and labels through natural language.3-
- AlicenseNot gradedqualityFmaintenanceEnables language models to manage Todoist tasks, projects, sections, labels, comments, and collaborators through natural language via the Model Context Protocol.MIT
- AlicenseNot gradedqualityDmaintenanceEnables Claude to manage Todoist tasks and projects, including creating, listing, updating, completing tasks, and managing projects with natural language.26 npmMIT
- AlicenseAqualityDmaintenanceConnect AI agents to your Todoist tasks via the Model Context Protocol (MCP).281MIT
- AlicenseAqualityDmaintenanceEnables natural language task management with Todoist, supporting tasks, projects, sections, labels, smart search, and batch operations for efficient workflow integration with Claude and other MCP-compatible LLMs.197 npmMIT
- AlicenseNot gradedqualityFmaintenanceA Model Context Protocol server that enables advanced task and project management in Todoist via Claude Desktop and other MCP-compatible clients.195 npm2MIT
TDQS
Scored across 33 tools
Multiple tools have overlapping purposes, causing confusion. For example, there are three separate search tools (search_tasks, search_tasks_using_and, search_tasks_using_or) that could be consolidated, and several 'list_' tools (e.g., list_brian_time_sensitive_tasks, list_becky_time_sensitive_tasks) are very similar in function but differ only by user or filter. This overlap makes it difficult for an agent to choose the right tool without deep context.
The naming is mixed but somewhat readable. Most tools use snake_case and start with verbs like 'get_', 'list_', 'create_', 'update_', 'complete_', which is consistent. However, there are inconsistencies such as 'complete_becky_task' vs. 'complete_task' (one is specific, the other general) and 'search_tasks' vs. 'search_tasks_using_and' vs. 'search_tasks_using_or' (redundant naming). Overall, the pattern is discernible but not fully uniform.
With 33 tools, the count is excessive for a Todoist server, indicating poor scoping. Many tools are highly specific (e.g., get_chores_due_today, get_tickler_tasks) and could be generalized into fewer, more flexible tools. This bloated set increases complexity and reduces usability, as agents must navigate numerous similar tools for basic operations.
The tool surface covers core Todoist operations well, including CRUD for tasks (create, update, complete, uncomplete), project and label management, and various querying functions. However, there are minor gaps, such as no direct tool for deleting tasks or managing project settings beyond labels, which might require workarounds but doesn't severely hinder functionality.