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damientilman

Mailchimp MCP

list_store_customers

Retrieve e-commerce store customers with order counts, total spend, and opt-in status to analyze purchasing behavior and identify high-value customers.

Instructions

List customers from a connected e-commerce store with order counts, total spend, and opt-in status.

Use to analyze customer purchasing behavior or identify high-value customers. Requires an active e-commerce integration. Use list_ecommerce_stores to find store IDs. Use list_store_orders for per-order detail instead of customer-level aggregates.

Authenticated via API key. Subject to Mailchimp API rate limits (max 10 concurrent requests). Read-only, safe to retry.

Args: store_id: The e-commerce store ID. Obtain from list_ecommerce_stores. count: Number of customers to return (1-1000, default 20). offset: Pagination offset. Use when total_items exceeds count.

Returns: JSON with total_items and customers array. Each customer: id (string), email_address, first_name, last_name, orders_count (int), total_spent (float, in store currency), opt_in_status (boolean), created_at (ISO 8601).

Example: list_store_customers(store_id="store123", count=50) -> {"total_items": 500, "customers": [{"email_address": "jane@co.com", "orders_count": 5, "total_spent": 299.95, ...}]}

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?

With no annotations provided, the description fully covers behavioral traits: authentication method ('Authenticated via API key'), rate limits ('Subject to Mailchimp API rate limits (max 10 concurrent requests)'), and read-only safety ('Read-only, safe to retry'). It also explains pagination and return format.

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 (about 10 lines) and well-structured: a one-sentence summary, usage paragraph, behavioral notes, Args/Returns sections, and an example. Every sentence serves a purpose with no repetition or fluff.

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?

Given the 3 parameters, no output schema, and no annotations, the description is remarkably complete. It includes return format in the Returns section, an example, and covers all aspects needed for an agent to select and invoke the tool correctly.

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?

Despite 0% schema description coverage, the description provides detailed parameter explanations in an Args section: store_id (how to obtain), count (range and default), offset (pagination usage). This fully compensates for the schema's lack of parameter descriptions.

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 verb ('list') and resource ('customers from a connected e-commerce store') and specifies the data included (order counts, total spend, opt-in status). It explicitly distinguishes from sibling tools by referencing list_store_orders for per-order detail and list_ecommerce_stores for finding store IDs.

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?

The description provides explicit use cases ('analyze customer purchasing behavior or identify high-value customers'), prerequisites ('Requires an active e-commerce integration'), and direct references to alternative tools ('Use list_ecommerce_stores to find store IDs. Use list_store_orders for per-order detail instead of customer-level aggregates').

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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