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damientilman

Mailchimp MCP

delete_member

Permanently delete a member and all associated data from a Mailchimp audience. Use for GDPR right-to-erasure requests; this action is irreversible.

Instructions

Permanently delete a member and all their data from an audience.

Use only for complete data removal (e.g. GDPR right-to-erasure requests). All activity history, merge field data, and tag associations are permanently lost. Use unsubscribe_member instead to stop sending while preserving data for reporting. There is no undo.

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. email_address: Email address of the member to permanently delete. Must exist in the audience.

Returns: JSON with fields: status ("permanently_deleted"), email_address. Returns error if the member does not exist.

Example: delete_member(list_id="abc123", email_address="jane@co.com") -> {"status": "permanently_deleted", "email_address": "jane@co.com"}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
list_idYes
email_addressYes

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 thoroughly discloses permanence, data loss, authentication, rate limits, dry-run modes, and error behavior. All relevant behavioral traits are covered.

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 well-organized with a clear purpose sentence, usage guidance, behavioral details, parameter definitions, return value, and example. Every sentence adds value without redundancy.

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?

The description covers all necessary aspects for a destructive tool: irreversible, data implications, parameter details, return structure, error handling, and a concrete example. No gaps remain.

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?

With 0% schema description coverage, the description provides full parameter context: list_id explanation with example and source, email_address requirement and existence condition. This compensates completely.

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 permanently deletes a member and all their data, contrasting with unsubscribe_member. The verb and resource are specific and 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 instructs use only for complete data removal (e.g., GDPR), directs to use unsubscribe_member for preserving data, and warns there is no undo. Context and alternatives are well specified.

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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