Enhanced Todoist MCP Server Extended

todoist_quick_add_task

Create Todoist tasks using natural language input to quickly add tasks with due dates, projects, and labels through text parsing.

Instructions

Create a task using Todoist's Quick Add feature with natural language parsing

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "text": "<text>"
    },
    "name": "todoist_quick_add_task"
  }
}

Input Schema

Name	Required	Description
`text`	Yes	Natural language text for quick task creation (e.g., 'Buy milk tomorrow at 2pm #shopping')
`note`	No	Additional note for the task (optional)
`reminder`	No	Reminder time (optional)

Schema Changelog

Changes observed during successful MCP inspections.

First observedJun 12, 2025

TDQS

A3.7/5.0

Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'natural language parsing' but doesn't cover critical aspects like required permissions, error handling, rate limits, or what happens on success/failure. For a creation tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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?

The description is a single, efficient sentence that front-loads the core purpose without unnecessary words. Every part ('Create a task,' 'Todoist's Quick Add feature,' 'natural language parsing') contributes essential information, making it maximally concise and well-structured.

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

Completeness3/5

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

Given the tool's moderate complexity (creation with natural language parsing), no annotations, and no output schema, the description is minimally adequate. It covers the what and how but lacks details on behavioral traits, error cases, or output format, which would be needed for full contextual understanding.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already documents all three parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema, such as formatting examples for 'reminder' or constraints on 'text.' This meets the baseline for high schema coverage.

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?

The description clearly states the specific action ('Create a task') using a specific method ('Todoist's Quick Add feature with natural language parsing'), which distinguishes it from the sibling 'todoist_create_task' that likely uses structured inputs. It specifies both the verb and resource with unique implementation details.

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

Usage Guidelines4/5

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

The description implies when to use this tool by mentioning 'natural language parsing,' suggesting it's for quick, informal task creation versus structured alternatives. However, it doesn't explicitly state when not to use it or name specific alternatives like 'todoist_create_task,' leaving some ambiguity.

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