apple-mail-mcp

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triage_inbox

Classify and summarize multiple inbox emails in one call, returning a priority-sorted list to give you a rapid overview of a busy mailbox.

Instructions

Classify and summarize multiple emails from a mailbox in one call using the configured local AI model. Returns a JSON array sorted by priority. Useful for getting a quick overview of a busy inbox.

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": "triage_inbox"
  }
}

Input Schema

Name	Required	Description	Default
`limit`	No	Number of recent messages to triage (max 20, default 10).
`account`	Yes	Account name, e.g. "iCloud". Use list_folders to discover accounts.
`mailbox`	No	Mailbox to triage. Defaults to "INBOX".	INBOX

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.1.0Aug 4, 2026

TDQS

A4.2/5.0

Behavior4/5

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

Without annotations, the description handles behavioral disclosure. It reveals the use of a configured local AI model, the bulk nature of the operation, and the output format (JSON array sorted by priority). This gives meaningful insight beyond the schema, though it does not explicitly state that emails are not modified.

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 three short, information-dense sentences covering action, return format, and use case. No filler or redundancy, making it easy to parse quickly.

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?

For a tool with no annotations and no output schema, the description covers essential aspects: what it does, the AI model dependency, bulk behavior, return format, and use case. It could delve deeper into output structure or side effects, but it is sufficient for initial tool selection and invocation.

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

Parameters3/5

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

The input schema includes descriptions for all three parameters (100% coverage), so the description does not need to add parameter details. It mentions 'mailbox' generically but adds no specific syntax or constraints beyond the schema, keeping the baseline at 3.

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 (classify and summarize), the resource (multiple emails from a mailbox), and distinguishes from siblings by emphasizing bulk processing in one call. It specifically says 'multiple emails' and 'one call', which differentiates it from single-email tools like summarize_email.

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?

The description provides a clear context for usage: 'getting a quick overview of a busy inbox.' However, it does not explicitly mention alternatives or when not to use, so it lacks full exclusionary guidance.

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