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Qualtrics MCP Server

Qualtrics MCP Server

by yrvelez
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

create_thank_you

Send or schedule a thank-you email to respondents in an existing distribution by providing email details and a message template.

Instructions

Send or schedule a thank-you email for respondents in an existing email distribution

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": {
      "distributionId": "<distributionId>",
      "fromEmail": "<fromEmail>",
      "fromName": "<fromName>",
      "replyToEmail": "<replyToEmail>",
      "subject": "<subject>",
      "messageId": "<messageId>",
      "libraryId": "<libraryId>"
    },
    "name": "create_thank_you"
  }
}

Input Schema

NameRequiredDescriptionDefault
subjectYesThank-you email subject line
fromNameYesFrom name displayed in the email
sendDateNoScheduled send date (ISO format); omit to send immediately
fromEmailYesVerified sender email address
libraryIdYesID of the library containing the message template
messageIdYesID of the thank-you message template
embeddedDataNoOptional tags for distribution reporting; these are not survey-flow embedded data
replyToEmailYesReply-to email address
distributionIdYesThe parent distribution ID

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4/5.0
Behavior4/5

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

Annotations indicate destructiveHint: false, meaning non-destructive. The description adds context about scheduling (sendDate) and that the email targets respondents. No contradictions with annotations.

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 concise sentence with no extraneous information. Every word is necessary.

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 9 parameters, 7 required, and no output schema, the description adequately covers the core action. However, it omits details about response behavior (e.g., what happens after sending) and edge cases like past sendDate.

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?

All 9 parameters have schema descriptions (100% coverage), so the description adds minimal value. It mentions embeddedData as optional tags, but does not clarify relationship between messageId and libraryId beyond what the schema provides.

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 verb (send or schedule) and resource (thank-you email for respondents in an existing email distribution). It distinguishes from sibling tools like create_email_distribution, which creates the distribution itself.

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 sending thank-you emails but does not explicitly state when to use this tool versus alternatives (e.g., create_reminder). No usage context or exclusions are provided.

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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