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Qualtrics MCP Server

Qualtrics MCP Server

by yrvelez
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TypeScript
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list_library_surveys

Read-only

List reusable survey templates stored in a Qualtrics library to discover and select complex survey definitions for copying or recreating.

Instructions

List reusable survey surveys in a Qualtrics library. Use these templates to discover complex survey definitions before copying or recreating them through MCP.

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": {
      "libraryId": "<libraryId>"
    },
    "name": "list_library_surveys"
  }
}

Input Schema

NameRequiredDescriptionDefault
offsetNoPagination offset
libraryIdYesThe library ID

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4/5.0
Behavior3/5

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

The annotations already declare readOnlyHint=true, indicating a safe read operation. The description adds no further behavioral details (e.g., pagination behavior, rate limits), providing only basic transparency beyond what annotations offer.

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 two sentences, with the first sentence front-loading the purpose and the second providing usage context. There is no redundant or unnecessary information, every sentence earns its place.

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?

Given the simplicity of the tool (2 parameters, no output schema, good annotations), the description covers the essential purpose and usage context. Minor gaps exist, such as not explaining the return format, but overall it is sufficiently complete for an AI agent to select and invoke the tool correctly.

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 coverage is 100% with descriptions for both libraryId and offset. The description does not enhance or add meaning to these parameters beyond what the schema provides, so it meets the baseline without adding extra value.

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 specifies the verb 'List' and the resource 'reusable survey surveys in a Qualtrics library', and distinguishes itself from sibling tools like list_surveys by focusing on library templates. The use case 'discover complex survey definitions before copying or recreating' further clarifies its unique purpose.

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 states when to use the tool ('before copying or recreating them through MCP'), providing clear context. However, it lacks explicit exclusions or mention of alternative tools for other scenarios, such as using list_surveys for actual surveys.

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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