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Mailchimp MCP by InsightfulPipe

Mailchimp Prompts

prompts_menu
Read-only

Browse the Mailchimp prompt catalog.

  1. request='menu' – List public/system prompts (optionally pass workspace_id + prompt_type).

  2. request='prompt_details' – Fetch prompt body by prompt_id. Set is_custom=True + workspace_id for workspace prompts.

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": {
      "request": "<request>"
    },
    "name": "prompts_menu"
  }
}

Input Schema

NameRequiredDescriptionDefault
requestYes
is_customNo
prompt_idNo
prompt_typeNo
workspace_idNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

The readOnlyHint annotation already establishes safety, and the description adds useful mode-specific behavior: public/system prompts are listed under 'menu', and workspace prompts require is_custom=True plus workspace_id under 'prompt_details'. It does not cover pagination, rate limits, or output shape, but those are partly mitigated by the output schema.

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 short, front-loaded, and organized as two numbered mode-specific instructions. Every sentence contributes directly to selecting and invoking the tool.

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

Completeness4/5

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

Given the readOnlyHint annotation and the presence of an output schema, the description is nearly complete for a two-mode prompt catalog tool. It covers the main selection logic and parameter conditions, with only minor gaps around return-value expectations and pagination behavior.

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

Parameters4/5

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

With 0% schema description coverage, the description does meaningful work by explaining all five parameters in context: request modes, optional prompt_type/workspace_id for menu, prompt_id for details, and is_custom plus workspace_id for workspace prompts. It could be stronger by describing allowed prompt_type values or default behavior, but it substantially compensates for the schema gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific resource (Mailchimp prompt catalog) and concrete verbs for each mode: listing public/system prompts and fetching a prompt body. It is clear on its own, though it does not explicitly contrast itself with sibling tools such as query_data or execute_action.

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

Usage Guidelines4/5

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

It clearly explains when to use each request value: 'menu' lists public/system prompts, while 'prompt_details' fetches a prompt body by prompt_id. It also notes the custom/workspace condition, but does not state exclusions or alternatives beyond the enum branches.

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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