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damientilman

Mailchimp MCP

create_interest

Add a new selectable interest option to an existing category, such as adding 'Tech' to 'Topics', making it available on signup forms.

Instructions

Create a new interest option within an interest category (e.g. add "Tech" to a "Topics" category).

Use after create_interest_category to add selectable options. Each option becomes available on signup forms (unless category type is 'hidden'). Use list_interests to check existing options. Use delete_interest to remove an option.

Authenticated via API key. Subject to Mailchimp API rate limits (max 10 concurrent requests). Respects read-only and dry-run modes.

Args: list_id: The Mailchimp audience/list ID (e.g. 'abc123def4'). Obtain from list_audiences. category_id: The interest category ID. Obtain from list_interest_categories or create_interest_category. name: Display name for the interest option (e.g. 'Tech', 'Sports'). Must be unique within the category.

Returns: JSON with fields: id (string, use with delete_interest), name, subscriber_count (int, starts at 0).

Example: create_interest(list_id="abc123", category_id="cat456", name="Technology") -> {"id": "int789", "name": "Technology", "subscriber_count": 0}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
list_idYes
category_idYes
nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

No annotations, but description adds authentication method (API key), rate limits (max 10 concurrent), and respect for read-only/dry-run modes. Also explains the option's availability on signup forms based on category type.

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 main purpose, usage context, auth, parameter details, return, and example. Slightly verbose but logical and front-loaded.

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?

Comprehensive: covers workflow, prerequisites, return value, and example. Given the 3 required parameters and output schema mentioned, description is complete enough.

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?

Schema coverage is 0%, but description explains each parameter: list_id from list_audiences, category_id from list_interest_categories/create_interest_category, and name with uniqueness constraint.

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 'create', the resource 'interest option', and the context 'within an interest category'. It differentiates from siblings like create_interest_category and list_interests.

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?

Explicitly instructs to use after create_interest_category and provides alternatives: list_interests to check existing options and delete_interest to remove. Also notes condition about hidden categories.

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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