Mailchimp MCP Server

list_store_promo_codes

Retrieve all promo codes for a specific promo rule in a connected Mailchimp store, enabling easy management of discounts and offers.

Instructions

List promo codes for a specific promo rule in a connected store.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "store_id": "<store_id>",
      "promo_rule_id": "<promo_rule_id>"
    },
    "name": "list_store_promo_codes"
  }
}

Input Schema

Name	Required	Description	Default
`store_id`	Yes
`promo_rule_id`	Yes
`count`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Addedv0.2.0May 2, 2026

TDQS

C2.9/5.0

Behavior2/5

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

No annotations are provided, and the description does not disclose any behavioral traits such as whether the operation is read-only, required authentication, rate limits, or side effects. For a list operation, it is likely safe but this is not communicated.

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 extremely concise, consisting of a single clear sentence with 12 words. It is front-loaded with the verb and directly conveys the tool's purpose without unnecessary words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite having an output schema, the description lacks context about pagination (count parameter), ordering, or the relationship between store and promo rule. It does not explain what a promo code is or how the list is populated, leaving gaps for the AI agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, meaning the description adds no information about the parameters. The input schema has titles but no descriptions, and the description does not explain the meaning or format of store_id, promo_rule_id, or count. This is insufficient for the AI agent.

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 action (list), the resource (promo codes), and the context (for a specific promo rule in a connected store). It distinguishes this tool from sibling list tools like list_members or list_audiences by specifying the exact entity and its parent relationship.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives or when not to use it. It does not mention required prerequisites (e.g., the store must be connected) or compare to similar tools like list_store_products or list_campaigns.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server