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Mailchimp MCP Server

Mailchimp MCP Server

by AlexlaGuardia
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_ecommerce_customer

Retrieve e-commerce customer details such as total order count and amount spent by specifying the store and customer ID.

Instructions

Get e-commerce customer details including order count and total spent.

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": {
      "store_id": "<store_id>",
      "customer_id": "<customer_id>"
    },
    "name": "get_ecommerce_customer"
  }
}

Input Schema

NameRequiredDescriptionDefault
store_idYes
customer_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 must fully disclose behavioral traits. However, it only mentions return fields without discussing side effects, authentication, rate limits, or other traits. For a read operation, it's insufficiently transparent.

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, front-loaded sentence of 9 words with no redundancy. Every word adds value.

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?

Given the output schema exists, the description need not explain return values. However, with two required params and no annotations, the description lacks prerequisites or error context. It is minimally complete for a simple retrieval tool.

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 should add meaning. It does not explain what 'store_id' and 'customer_id' represent or how to obtain them. The parameter names are self-explanatory but the description adds no extra value beyond the names.

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 specifies the verb 'Get' and the resource 'e-commerce customer details', and adds specifics ('order count and total spent'). It clearly distinguishes this tool from sibling tools like 'get_member' or 'list_store_customers' (though the latter is not a sibling, the context makes the purpose clear).

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 when to use (to retrieve a single customer's details) but provides no explicit guidance on when not to use or alternatives. Given the sibling list includes 'search_members' and 'list_members', but those are for different entities. Minimal guidance.

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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