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Mailchimp MCP

Mailchimp MCP

by damientilman
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python

describe_tools

Read-only

List tools with risk classifications—read, write, destructive—to enforce access policies. Read-only and safe to retry.

Instructions

List every tool with its machine-readable risk classification for policy enforcement.

Use this to discover which tools are reads, reversible writes, or destructive (irreversible) before granting access or building automation. A runtime-security gateway can also read the same signal from the MCP tool annotations (readOnlyHint / destructiveHint / idempotentHint) exposed via tools/list; this tool is the convenience, tool-call-based view of that metadata.

No network call. Read-only, safe to retry.

Returns: JSON with summary (counts per risk tier and destructive total) and tools array. Each: name, risk ('read' | 'write' | 'destructive'), read_only (bool), destructive (bool), idempotent (bool).

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "describe_tools"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.7.1

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, but the description adds 'No network call. Read-only, safe to retry,' providing context about behavior and retry safety beyond annotations. 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?

Concise and well-structured: a clear purpose statement, usage guidance, behavioral note, and a structured Returns section. Every sentence adds value with no redundancy.

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 zero parameters and an output described clearly, the description is complete. It explains the tool's purpose, usage context, behavior, and return format, enabling full understanding.

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?

Input schema has zero parameters, so parameter semantics are not applicable. However, the description explains the return structure in detail (summary and tools array), which adds value beyond the schema.

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 starts with 'List every tool with its machine-readable risk classification for policy enforcement,' which clearly states the verb and resource. It also distinguishes from the tools/list endpoint, enhancing clarity among siblings.

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?

Explicitly states when to use: 'Use this to discover which tools are reads, reversible writes, or destructive... before granting access or building automation.' Also mentions an alternative (tools/list), but does not explicitly say when not to use, which would be ideal.

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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