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Mailchimp MCP

Mailchimp MCP

by damientilman
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python

delete_store_order

DestructiveIdempotent

Permanently delete an e-commerce order from a store. This action removes the order and its lines and cannot be undone.

Instructions

Permanently delete an e-commerce order from a store.

This removes the order and its lines and cannot be undone. Manual commerce writes suit custom/headless stores; Shopify and WooCommerce integrations sync orders automatically.

Args: store_id: E-commerce store ID. Obtain from list_ecommerce_stores. order_id: Order ID to delete.

Returns: JSON confirming deletion (empty body on success) or an error object.

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>",
      "order_id": "<order_id>"
    },
    "name": "delete_store_order"
  }
}

Input Schema

NameRequiredDescriptionDefault
accountNo
order_idYes
store_idYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.7.1

TDQS

A4.6/5.0
Behavior5/5

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

The description adds value beyond annotations by detailing that the order and its lines are permanently removed and that the action cannot be undone. Annotations already indicate destructive and idempotent hints, and these descriptions align without contradiction.

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 concise and well-structured: a clear purpose statement, effect and caution, store type context, and an Args/Returns section. Every sentence provides value without redundancy.

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 description covers the destructive nature, scope of deletion, how to get parameters, and expected return. It could mention error cases (e.g., order not found), but given the simple delete operation, it is reasonably complete.

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

Parameters4/5

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

The description explains the two required parameters (store_id and order_id) and how to obtain store_id from list_ecommerce_stores. The optional 'account' parameter is not mentioned, but with 0% schema coverage, the description compensates well for the critical parameters.

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's action: 'Permanently delete an e-commerce order from a store.' It specifies the verb (delete) and the resource (order), and distinguishes it from siblings by focusing on orders, not carts or customers.

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 advises that the operation cannot be undone and provides context about store types (manual vs. integrated), implying when to use it. However, it does not explicitly state when not to use it or compare to alternatives like update actions.

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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