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Mailchimp MCP

Mailchimp MCP

by damientilman
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python

get_survey_response

Read-only

Retrieve the details and answers of a specific survey response by providing the survey and response IDs. Inspect individual respondent data.

Instructions

Get a single survey response.

Retrieves the details of one specific response submitted to the specified survey. Use this to inspect the answers of an individual respondent.

Args: survey_id: The unique id of the survey. response_id: The unique id of the response to retrieve.

Returns: JSON with the survey response details.

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>",
      "response_id": "<response_id>"
    },
    "name": "get_survey_response"
  }
}

Input Schema

NameRequiredDescriptionDefault
accountNo
survey_idYes
response_idYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.7.1

TDQS

A3.9/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, so the description adds minimal behavioral disclosure beyond that. It confirms the tool retrieves response details but does not mention any side effects, rate limits, or authorization needs.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is reasonably concise with a clear structure (brief title, paragraph, Args/Returns sections). The Args section is somewhat redundant with the schema but adds brevity.

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?

For a simple read-only tool with annotations and an output schema, the description covers the main points. The omission of the optional account parameter is a minor gap, but overall it is complete enough for an agent to understand and invoke.

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 0%, so the description must compensate. It explains survey_id and response_id briefly but omits the optional account parameter completely. Thus, it adds partial meaning but is incomplete.

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 retrieves a single survey response, using specific verbs ('Get', 'inspecting answers') and the resource ('survey response'). It distinguishes from sibling tools like get_survey_responses (list) and get_survey.

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 explicitly states to use this tool to inspect individual respondent answers, implying when to use vs. listing all responses. It does not explicitly state when not to use, but the context is clear.

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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