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surveymonkey-mcp

surveymonkey-mcp

by dscovr
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

surveymonkey_get_survey

Retrieve metadata for a specific survey, including title, response count, and dates. Use to check survey status or performance without question details.

Instructions

Returns metadata for a specific survey (title, response count, dates, etc.). Does NOT include questions — use surveymonkey_get_survey_details for that.

Args: survey_id: Survey ID.

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": {
      "survey_id": "<survey_id>"
    },
    "name": "surveymonkey_get_survey"
  }
}

Input Schema

NameRequiredDescriptionDefault
survey_idYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses the return behavior (metadata fields) and an exclusion (no questions), which is useful. It does not mention side effects or permissions, but for a simple get operation this is adequate. It adds value beyond the schema by clarifying scope.

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 plus an Args line, all front-loaded with the primary purpose and the key exclusion. There is zero waste and the structure makes it easy to scan.

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?

The tool is simple (one parameter, no nested objects) and has an output schema. The description covers what it returns, what it excludes, and how to get the excluded data. It doesn't mention prerequisites, but for a get-by-ID operation that is not critical. The description is complete for an agent to call it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. The Args section merely repeats the schema's 'Survey ID' without adding format, source, or usage hints. For a single simple parameter this is minimal but not enriching; it adds no meaning beyond what the schema already says.

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 states a specific verb and resource: 'Returns metadata for a specific survey' and enumerates the kind of data (title, response count, dates). It explicitly differentiates from the sibling surveymonkey_get_survey_details by saying it does NOT include questions, so an agent can tell them apart.

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

Usage Guidelines5/5

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

It explicitly says when not to use this tool and names the alternative: 'Does NOT include questions — use surveymonkey_get_survey_details for that.' This gives clear routing guidance. The context of when to use (when metadata is needed) is implied but unambiguous.

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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