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Qualtrics MCP Server

Qualtrics MCP Server

by yrvelez
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
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estimate_export_size

Read-only

Estimate the size of survey exports by supplying the question count and optional response count. Omitting the response count provides a per-response estimate.

Instructions

Estimate export size from the survey's question count and an optional expected response count. Qualtrics survey metadata does not expose response totals, so omitting expectedResponseCount returns an honest per-response estimate.

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": {
      "surveyId": "<surveyId>"
    },
    "name": "estimate_export_size"
  }
}

Input Schema

NameRequiredDescriptionDefault
formatNoExport format to estimate (default: json)
surveyIdYesThe Qualtrics survey ID
expectedResponseCountNoExpected number of responses; omit for a per-response estimate

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true. The description adds value by explaining the tool returns an honest per-response estimate when expectedResponseCount is omitted, and clarifies that survey metadata doesn't expose response totals. No contradiction.

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 sentences, front-loaded with purpose, followed by essential context. No wasted words, highly efficient.

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?

The description covers input behavior well but lacks any details about the output format of the estimate (e.g., size in bytes or string). With no output schema, this omission reduces completeness for a simple tool.

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 parameters well. The description adds minimal semantic value beyond restating what the schema says, resulting in a baseline score.

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 tool estimates export size using question count and optional expected response count, distinguishing it from other tools. It is a specific verb+resource.

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?

The description implies usage for estimation before actual export but does not explicitly compare to siblings like export_responses or provide when-not-to-use guidance. It offers context on expectedResponseCount but lacks alternatives.

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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