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greirson

Todoist MCP Server

todoist_task_quick_add

Create a Todoist task by typing natural language: the text is automatically parsed to set due dates, projects, labels, priorities, and descriptions.

Instructions

Create a task using natural language parsing like the Todoist app. The text is parsed to extract due dates, projects (#), labels (@), assignees (+), priorities (p1-p4), deadlines ({in 3 days}), and descriptions (//). Example: "Buy groceries tomorrow #Shopping @errands p1 {deadline Friday} //Don't forget milk"

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesThe task text with natural language. Can include: due dates (tomorrow, next Monday), project name starting with # (without spaces), label starting with @, assignee starting with +, priority (p1 = urgent, p2, p3, p4 = lowest), deadline between {} (e.g., {in 3 days}), description starting from // until end of text
noteNoAdditional note to add to the task (optional)
reminderNoReminder date in free form text like 'tomorrow at 9am' (optional)
auto_reminderNoWhen true, a default reminder is added if the task has a due date with time (optional, default: false)
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Discloses parsing behavior (extracts due dates, projects, etc.) and provides an example. However, no annotations are provided, and the description omits potential side effects, error handling, or idempotency. Does not specify return values.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two concise sentences: first states purpose, second summarizes syntax with a clear example. No extraneous information; every sentence contributes.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Adequately explains parsing capabilities and provides an example. Lacks information about return value (e.g., created task object) and how it differs from sibling tools like todoist_task_create, but sufficient for a quick-add tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema already covers 100% of parameter descriptions. The description adds value by providing a working example and summarizing the natural language syntax, though most details repeat the schema's text parameter description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states it creates a task using natural language parsing, distinguishing it from other task creation methods. Description provides specific verb ('Create') and resource ('task') with parsing approach.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Implied usage for quick natural language entry, but no explicit when-to-use or when-not-to-use compared to alternatives like todoist_task_create. Lacks guidance on appropriate contexts.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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