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damientilman

Mailchimp MCP

get_account_info

Retrieve Mailchimp account details like name, contact info, total subscribers, and industry benchmarks to verify API connectivity or inspect account-level metrics.

Instructions

Retrieve Mailchimp account details including name, contact info, total subscribers, and industry benchmarks.

Use this to verify API connectivity or inspect account-level metrics. Typically the first call in a workflow. Do not use this as a health check; use ping instead (faster, no payload). Use list_audiences to get per-audience stats.

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

Returns: JSON with fields: account_name (string), email (account owner), first_name, last_name, total_subscribers (int, all audiences combined), industry_stats (object with open/click rate benchmarks for the account's industry). Returns an error object if the API key is invalid or missing.

Example: get_account_info() -> {"account_name": "My Company", "total_subscribers": 5000, "industry_stats": {"open_rate": 0.21, ...}}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

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 discloses read-only nature, safety to retry, authentication via API key, and rate limit constraints (max 10 concurrent requests). Also mentions error handling for invalid/missing API key.

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?

Concise yet comprehensive: single paragraph with clear sections for purpose, usage, behavior, return fields, and example. 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 no annotations and no input parameters, the description fully covers all relevant aspects: purpose, usage guidance, behavioral traits, output format, and example. No gaps.

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 parameters, so no parameter details needed. Description adds value by explaining return fields and providing an example, exceeding the baseline for a no-param tool.

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?

Description clearly states it retrieves Mailchimp account details including name, contact info, total subscribers, and industry benchmarks. It distinguishes from siblings like ping (health check) and list_audiences (per-audience stats).

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 (verify API connectivity, inspect account-level metrics, first call in a workflow) and when not (use ping for health check, use list_audiences for per-audience stats), naming specific alternative tools.

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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