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TaskLite MCP

by tasklite-net
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TypeScript
Remote

create_board

Create a board in a project to track tasks or store custom data. Task boards include built-in columns for status, priority, assignee, due date, and tags; data boards start empty for your own columns.

Instructions

Create a board (a data table) inside a project. Add typed columns with create_column afterwards. kind: "tasks" (default) also gives the board the built-in task columns — status, priority, assignee, due date, tags — for work people track; "data" creates a plain table with only the columns you add, for records such as customers, products or orders (requires a TaskLite server from 2026-09-06; older servers ignore kind).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNo"tasks": with the built-in task columns (status, priority, assignee, due date, tags). "data": only the columns you add. Default tasks.
nameYesHuman-readable name
projectIdYesProject id (from list_projects / create_project)
descriptionNoFree-text description

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changedv0.13.0
    • addedInput schema / properties / description / description
      Added value: +"Free-text description"
    • addedInput schema / properties / kind
      Added value: +{
+  "description": "\"tasks\": with the built-in task columns (status, priority, assignee, due date, tags). \"data\": only the columns you add. Default tasks.",
+  "enum": [
+    "tasks",
+    "data"
+  ],
+  "type": "string"
+}
    • addedInput schema / properties / name / description
      Added value: +"Human-readable name"
    • addedInput schema / properties / projectId / description
      Added value: +"Project id (from list_projects / create_project)"
  2. First observedv0.7.0

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already indicate readOnlyHint: false and destructiveHint: false, so the mutation behavior is not new. The description adds valuable behavioral context beyond annotations: tasks boards include built-in columns, data boards contain only added columns, and older servers ignore the kind parameter. This version-dependent behavior is a useful disclosure that annotations do not capture.

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 compact and information-dense without fluff. It front-loads the core purpose, then addresses column creation and kind nuances, including the important version caveat. Every sentence contributes to correct invocation.

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?

The description covers the main purpose, kind behavior, defaults, server compatibility, and the relationship with create_column. It does not mention the return value or error cases, but given the simple create operation and rich schema, the essential context for an agent to select and invoke the tool is present.

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 description coverage is 100%, so the baseline is 3. The description adds meaningful semantics beyond the schema by explaining the difference between tasks and data with concrete examples and clarifying that columns are added separately. This enhances parameter understanding, especially for kind and its server-version constraint.

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 a specific action and resource: 'Create a board (a data table) inside a project.' It also differentiates board creation from later column creation with 'Add typed columns with create_column afterwards.' The two kinds, tasks and data, are explained with distinct use cases, so an agent can understand what the tool does relative to siblings.

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 provides clear selection context by explaining when to choose tasks vs data boards, including examples like work tracking versus customer/product records. It also signals that column definition is a separate step handled by create_column. It does not enumerate exclusions or mention alternatives like update_board, but the context is strong enough for correct use.

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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