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damientilman

Mailchimp MCP

list_store_carts

Retrieves a store's carts, including abandoned ones, with customer and total info. Use for abandoned-cart recovery workflows.

Instructions

List carts for a store, including abandoned ones, with customer and total info.

Carts in Mailchimp typically represent in-progress purchases synced from a connected storefront. Use for abandoned-cart workflows: filter by recent created_at, segment by cart total, then trigger a recovery automation. Use get_store_cart for a single cart with line items. Use list_store_orders for completed purchases.

Authenticated via API key. Max 10 concurrent requests. Read-only, safe to retry. Returns 404 if store_id is invalid.

Args: store_id: E-commerce store ID. Obtain from list_ecommerce_stores. count: Number of carts to return (1-1000, default 20). offset: Pagination offset.

Returns: JSON with store_id, total_items, and carts array. Each cart: id, customer (object with id, email_address, opt_in_status), currency_code, order_total, tax_total, checkout_url, created_at, updated_at.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
store_idYes
countNo
offsetNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

Despite no annotations, the description discloses key behaviors: read-only, safe to retry, max 10 concurrent requests, returns 404 for invalid store_id, and explains cart context (synced in-progress purchases). This fully informs the agent.

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?

Well-structured with front-loaded purpose, then context, usage, parameters, and behavior. However, it is somewhat verbose; could be tightened without losing information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Covers all aspects: purpose, usage scenarios, parameter details, behavioral constraints, and return format (though output schema is separate). No gaps given the tool's complexity and the lack of annotations.

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

Parameters5/5

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

The description adds significant meaning beyond the schema: explains how to obtain store_id, the valid range for count (1-1000, default 20), and offset for pagination. Schema has 0% description coverage, so this is critical and well done.

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 'List carts for a store' with specific details about including abandoned carts and customer/total info. It distinguishes from siblings like get_store_cart and list_store_orders, making the purpose unambiguous.

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?

Provides explicit guidance for abandoned-cart workflows, suggests filtering by created_at and cart total, and names alternatives (get_store_cart, list_store_orders). Also mentions prerequisite (store_id from list_ecommerce_stores) and use cases.

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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