quicksight-mcp

create_pivot_table

Create a QuickSight pivot table in a specified analysis sheet from row and value columns, aggregations, and a dataset identifier.

Instructions

Create a pivot table from simple parameters.

Input Schema

TableJSON Schema

Name	Required	Description
`title`	Yes	Display title.
`sheet_id`	Yes	The sheet to add the table to.
`analysis_id`	Yes	The QuickSight analysis ID.
`row_columns`	Yes	Comma-separated dimension columns for rows (e.g., "MARKET_NAME,ASSESSMENT_TYPE").
`value_columns`	Yes	Comma-separated measure columns for values (e.g., "FLIP_TOKEN,REVENUE").
`dataset_identifier`	Yes	The dataset identifier.
`value_aggregations`	Yes	Comma-separated aggregations, one per value (e.g., "COUNT,SUM").

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.1.0Sep 13, 2026

TDQS

C2.9/5.0

Behavior2/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It does not state that this is a mutating operation, what permissions or IDs are required, what happens to the target sheet, or how errors are surfaced; only the word 'Create' implies mutation.

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

Conciseness4/5

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

The definition is a single front-loaded sentence with no unnecessary repetition. However, 'from simple parameters' is vague filler and the brevity comes at the cost of useful detail.

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

Completeness2/5

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

For a 7-parameter required mutation tool with no annotations, the description is too thin. The output schema means return values need not be explained, but the description omits routing guidance, prerequisites, and behavioral context that an agent would need before invoking it.

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 all seven parameters are documented in the schema. The description adds no meaning beyond 'simple parameters' and does not explain relationships such as analysis_id/sheet_id or the row/value/aggregation structure. Baseline 3 is appropriate.

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

Purpose4/5

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

The description has a clear verb+resource: 'Create a pivot table.' It does not distinguish the tool from the many sibling creation tools such as create_table, create_kpi, or create_bar_chart, and the phrase 'from simple parameters' adds no specific scope.

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

Usage Guidelines2/5

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

No when-to-use guidance is provided. The description does not mention alternatives, prerequisites, or the circumstances under which a pivot table should be chosen over create_table or a calculated field.

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

Deploy Server