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s-morgan-jeffries

apple-mail-mcp

list_accounts

Read-onlyIdempotent

Lists all email accounts configured in Apple Mail, including their IDs, display names, email addresses, account type, and enabled status.

Instructions

List all configured email accounts in Apple Mail.

Returns each account's id (UUID), display name, email addresses, account type, and enabled state. Account ids are stable across name changes; prefer them over names for identifying accounts.

Returns: Dictionary containing the accounts list.

Example: >>> list_accounts() {"success": True, "accounts": [ {"id": "B21B254B-...", "name": "Gmail", "email_addresses": ["me@gmail.com"], "account_type": "imap", "enabled": True}, ... ]}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

The description adds value beyond annotations by detailing the return structure (id, name, email addresses, account_type, enabled state) and highlighting the stability of account ids. It also provides an example. Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the description complements them well.

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 concise and well-structured. It starts with a clear purpose sentence, then lists key return fields, followed by a Returns section and an example. 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?

The description is complete for a simple list tool with no parameters. It fully describes the return structure and includes an example, compensating for the absence of an explicit output schema. Given the low complexity, the description covers all necessary information.

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?

The tool has no parameters, and the input schema has 100% coverage with no additional description needed. The description does not need to add parameter semantics, and it appropriately omits any. Baseline score of 4 is suitable.

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 tool's action: 'List all configured email accounts in Apple Mail.' It specifies the resource (email accounts) and the scope (all configured). This distinguishes it from sibling tools like list_mailboxes or list_rules.

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. It does not mention prerequisites, exclusions, or comparison with sibling tools. The only usage-related advice is about preferring account ids over names, which pertains to using the output, not tool selection.

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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