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Apple Mail MCP

Apple Mail MCP

by cyberprive
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

list_mailboxes

Read-only

Lists mailboxes (folders) inside a specified Apple Mail account, optionally including unread and total message counts.

Instructions

List mailboxes (folders) inside an account.

Args: account: Account name as returned by list_accounts. with_counts: If true, include unread_count and total_count per mailbox. Slow on large accounts — Mail enumerates each folder to count messages. On a 30k-message iCloud account with 80+ folders this can take 30+ seconds. Default false.

Returns a list of {name, unread_count?, total_count?}.

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": {
      "account": "<account>"
    },
    "name": "list_mailboxes"
  }
}

Input Schema

NameRequiredDescriptionDefault
accountYes
with_countsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.5/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, yet the description adds substantive behavior the annotation cannot: with_counts triggers per-folder enumeration, with a concrete latency example (30k messages, 80+ folders, 30+ seconds). It also discloses the return shape, which no output schema provides.

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?

Front-loaded purpose sentence followed by parameter notes that each earn their place. Minor waste from the raw docstring 'Args:'/'Returns' formatting and a repeated default, but nothing misleading or padded.

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?

For a two-parameter read tool with no output schema, the description supplies the prerequisite, the performance trap, and the returned fields. An agent has everything needed to call it correctly and avoid the slow path.

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 description coverage is 0%, so the description carries the full burden and does so: 'account' is defined by its source tool, and 'with_counts' is explained in semantics, default, mechanism, and cost. Both parameters are fully usable without reading the schema.

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?

States a specific verb and resource ('List mailboxes (folders) inside an account') and even clarifies the mailbox/folder synonym. It ties itself to list_accounts via the account parameter, though it does not explicitly contrast itself with search_messages or other listing tools.

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?

Provides a real prerequisite ('account name as returned by list_accounts') and strong guidance on the optional parameter: default false, and only enable when counts are needed because it is slow on large accounts. Lacks an explicit 'use X instead' alternative, but the conditions are clear.

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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