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surveymonkey-mcp

surveymonkey-mcp

by dscovr
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

surveymonkey_create_contact_list

Create a new contact list in SurveyMonkey by providing a name, organizing recipients for future survey distributions.

Instructions

Creates a new contact list.

Args: name: Name for the new contact list.

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": {
      "name": "<name>"
    },
    "name": "surveymonkey_create_contact_list"
  }
}

Input Schema

NameRequiredDescriptionDefault
nameYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.1/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only restates the mutation ('creates') and does not mention permissions, duplicate-name behavior, idempotency, or what happens after creation.

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 extremely concise and well-structured: a one-sentence action followed by an Args block. Every part is useful, and there is no redundancy or filler.

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?

For a one-parameter create operation, the description is minimally viable, especially since an output schema exists. However, the absence of annotations and lack of usage or behavioral caveats leave meaningful gaps for an AI agent evaluating whether and how to invoke this 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?

The Args block gives the single parameter a role, 'name for the new contact list,' which adds a small amount of meaning beyond the schema's bare title. However, with 0% schema description coverage, it lacks useful details such as format, length, uniqueness, or constraints.

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 states a specific action and resource: 'Creates a new contact list.' This is clear and distinguishes the tool from sibling create tools by object type, though it does not explicitly contrast it with any sibling.

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?

There is no guidance on when to use this tool versus related contact or contact-list operations, nor any mention of prerequisites or exclusions. The only usage signal is implied by the verb 'creates,' which is insufficient among more than 40 sibling tools.

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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