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Mailchimp MCP Server

Mailchimp MCP Server

by AlexlaGuardia
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_ab_test_results

Retrieve the winning variation and performance metrics for your A/B test campaign, showing which combination had the best results.

Instructions

Get A/B test (variate) results for a campaign — which combination won and performance of each.

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": {
      "campaign_id": "<campaign_id>"
    },
    "name": "get_ab_test_results"
  }
}

Input Schema

NameRequiredDescriptionDefault
campaign_idYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.2.0

TDQS

B3.4/5.0
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. It indicates a read operation ('Get') but does not disclose potential side effects, authentication needs, rate limits, or other behavioral traits beyond the basic purpose.

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 efficient sentence with a dash providing extra detail. It is front-loaded and contains no redundant words.

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 simple tool with one parameter and an output schema (not shown), the description gives a reasonable overview. However, it lacks context on error handling, response structure beyond 'performance', and prerequisites. It is minimally adequate.

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?

With 0% schema description coverage, the description should compensate. It mentions only the tool's purpose, not the campaign_id parameter's meaning, format, or how to obtain it. The single parameter is straightforward, but no additional value is added.

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 uses a specific verb ('Get') and resource ('A/B test results for a campaign'), clearly distinguishing it from sibling tools like get_campaign_report or get_click_report. It also notes the outcome ('which combination won and performance of each').

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 the tool is for campaigns with A/B tests but does not explicitly state when to use it vs alternatives, nor does it mention prerequisites or exclusions. Guidance is only implicit.

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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