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damientilman

Mailchimp MCP

by damientilman
OverviewSchemaRelated ServersScoreDiscussions
Python

get_automation_summary

Combine two Mailchimp API calls into a single audit overview: count classic automations by status and recent automation campaigns with total emails sent and top titles.

Instructions

Summarise automation activity across Classic Automations and Customer Journeys.

Combines two API calls into a single overview useful for audits and dashboards:

  1. /automations to count Classic workflows by status (sending / paused / draft)

  2. /campaigns?type=automation&since_send_time=N days ago to count and sum what automations have actually sent recently (both Classic and Customer Journey emails show up as type='automation' campaigns)

This is the recommended starting point for "what's my automation stack doing right now?" questions during an account audit. Use list_automations for the raw Classic list. Use search_automation_campaigns for the raw recent automation campaign feed.

Authenticated via API key. Max 10 concurrent requests (2 are issued by this tool). Read-only, safe to retry.

Args: days: Lookback window in days for the recent-sends portion (1-365, default 30).

Returns: JSON with two sections: - classic_automations: total, by_status ({sending, paused, draft, ...}) - recent_automation_campaigns: window_days, total_campaigns, total_emails_sent, top_titles (up to 5 titles ordered by emails_sent desc)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Tool Definition Quality

A4.9/5.0
Behavior5/5

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

No annotations provided, but the description fully discloses that it combines two API calls, is read-only, safe to retry, and has concurrency limits (max 10, with 2 used).

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 clear sections, but slightly longer than necessary; some repetition of the two API calls in the returns section. Still, every sentence adds value.

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 complexity (combines two API calls), the description covers purpose, usage, behavior, parameters, auth, concurrency, and return structure comprehensively. Output schema is also described.

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 adds full meaning for the 'days' parameter: purpose, valid range (1-365), and default value. 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 summarizes automation activity across Classic Automations and Customer Journeys, with specific verbs and resources. It explicitly distinguishes from siblings list_automations and search_automation_campaigns.

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 it is the recommended starting point for 'what's my automation stack doing right now?' and directs when to use list_automations and search_automation_campaigns instead.

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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