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damientilman

Mailchimp MCP

get_automation_email_queue

Retrieve subscribers queued to receive a specific automation email, with scheduled send times. Use automation ID and email ID from prior calls.

Instructions

Retrieve the queue of subscribers about to receive a specific automation email, with scheduled send times.

Use to see who is waiting to receive a particular email in a workflow. Use get_automation_emails first to find email_id values within the workflow.

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

Args: automation_id: The automation workflow ID (e.g. 'auto123'). Obtain from list_automations. email_id: The specific email ID within the automation. Obtain from get_automation_emails.

Returns: JSON with total_items (int) and queue array. Each entry: email_address (string), next_send (ISO 8601 timestamp of scheduled send).

Example: get_automation_email_queue(automation_id="auto123", email_id="email456") -> {"total_items": 12, "queue": [{"email_address": "jane@co.com", "next_send": "2025-06-02T10:00:00Z"}]}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
automation_idYes
email_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

No annotations provided, but description fully covers: authenticated via API key, subject to rate limits (max 10 concurrent), read-only and safe to retry. No contradictions.

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 clear sections (Args, Returns, Example). Concise yet informative, no superfluous content.

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?

For a simple read tool, covers all: authentication, rate limits, parameter sources, return format with example. Output schema present but description adds context.

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 description coverage 0%, but description explains each parameter in Args, including how to obtain them (list_automations, get_automation_emails). Adds significant value.

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 'Retrieve the queue of subscribers about to receive a specific automation email'. Specific verb and resource, distinguishes from siblings like get_automation_emails.

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 says when to use: to see who is waiting for a workflow email. Instructs to first call get_automation_emails. Also mentions authentication and rate limits.

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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