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Mailchimp MCP

create_interest_category

Create a container for interest options in a Mailchimp audience to organize subscriber preferences on signup forms.

Instructions

Create a new interest category (group container) in an audience for organizing subscriber preferences.

Use to create a container for interest options. Typical workflow: create_interest_category -> create_interest (add options within the category). The type controls how subscribers interact with it on signup forms. Use list_interest_categories to check existing categories first.

Args: list_id: The Mailchimp audience/list ID (e.g. 'abc123def4'). Obtain from list_audiences. title: Display title for the category (e.g. 'Preferred Topics'). Must be unique within the audience. type: How the category appears on signup forms. Valid values: 'checkboxes' (subscribers can select multiple), 'dropdown' (single select), 'radio' (single select), 'hidden' (not shown on forms, managed via API only).

Returns: JSON with fields: id (string, use with create_interest, list_interests, delete_interest_category), title, type, list_id.

Example: create_interest_category(list_id="abc123", title="Newsletter Preferences", type="checkboxes") -> {"id": "cat456", "title": "Newsletter Preferences", "type": "checkboxes", ...}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYes
titleYes
accountNo
list_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Annotations already indicate non-readonly, non-idempotent, non-destructive. The description adds behavioral context: the title must be unique, type controls form interaction, and the operation creates a container. It does not conflict with annotations and provides useful constraints beyond them.

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 (~150 words) and well-structured: summary sentence, usage guidance, Args, Returns, Example. Every sentence adds value, with no fluff. The format makes it easy for an agent to parse.

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 tool's moderate complexity and the presence of an output schema, the description is complete. It explains the workflow, parameter roles, return value fields, and provides an example. All necessary information for correct invocation is present.

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?

Schema coverage is 0%, so the description compensates well. It defines three required parameters (list_id, title, type) with examples and valid values for type. The optional 'account' parameter is not described, but it is default null and not required. The description covers the key parameters thoroughly.

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 purpose: 'Create a new interest category (group container) in an audience for organizing subscriber preferences.' It specifies the verb (create), resource (interest category), and its role as a container. It distinguishes from sibling create_interest by describing the typical workflow, avoiding confusion.

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 explains when to use the tool ('to create a container for interest options'), provides a typical workflow (create_interest_category -> create_interest), and suggests checking existing categories with list_interest_categories. It gives guidance on the type parameter's behavior. It does not explicitly state when not to use, but the context is sufficient.

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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