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damientilman

Mailchimp MCP

delete_interest

Delete a single interest option from a Mailchimp audience category. The interest and its subscriber associations are removed permanently.

Instructions

Delete a single interest option from a category, keeping the category and other options intact.

Use to remove one specific option. The interest and its subscriber associations are removed. Use delete_interest_category instead to remove the entire category with all options at once.

Authenticated via API key. Subject to Mailchimp API rate limits (max 10 concurrent requests). This operation is irreversible. 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. interest_id: The interest option ID to delete. Obtain from list_interests.

Returns: JSON with fields: status ("deleted"), interest_id. Returns error if interest does not exist.

Example: delete_interest(list_id="abc123", category_id="cat456", interest_id="int789") -> {"status": "deleted", "interest_id": "int789"}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
list_idYes
category_idYes
interest_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

With no annotations, description carries full burden. It discloses authentication via API key, rate limits (max 10 concurrent), irreversibility, and respect for read-only/dry-run modes—comprehensive behavioral context.

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?

Well-structured with sections (description, usage, args, returns, example). Each sentence adds value; no fluff. Efficiently packs necessary 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?

No annotations, but description covers safety, return values, example, and prerequisites for obtaining IDs. Output schema exists and description aligns with it. Complete for an irreversible delete operation.

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?

Input schema has zero description coverage; description compensates fully by detailing each parameter's meaning, how to obtain them (e.g., 'Obtain from list_audiences'), and provides an example with realistic IDs.

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?

Clearly states it deletes a single interest option from a category while keeping the category intact. Differentiates from sibling tool delete_interest_category, making 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?

Explicitly describes when to use (remove one specific option) and when not (use delete_interest_category for entire category). Provides clear alternative and usage context.

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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