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isityael

Apple Mail MCP Server

by isityael

compose_email

Create and send new messages from a specified mail account, with attachments, CC/BCC, and HTML. Choose immediate send, draft, or review.

Instructions

Compose and send a new email from a specific account.

Args: account: Account name to send from (e.g., "Gmail", "Work", "Personal") to: Recipient email address(es), comma-separated for multiple subject: Email subject line body: Email body text (plain-text fallback when body_html is used) cc: Optional CC recipients, comma-separated for multiple bcc: Optional BCC recipients, comma-separated for multiple attachments: Optional file paths to attach, comma-separated for multiple (e.g., "/path/to/file1.png,/path/to/file2.pdf") mode: Delivery mode — "send" (send immediately, default), "draft" (save silently to Drafts), or "open" (open compose window for review before sending) body_html: Optional HTML email body for rich formatting

Returns: Confirmation message with details of the email

User Preferences: {"workflow": "default", "notifications": "enabled"}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ccNo
toYes
bccNo
bodyYes
modeNosend
accountYes
subjectYes
body_htmlNo
attachmentsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations provided, so the description carries the full burden. It discloses modes (send/draft/open), plain-text fallback with body_html, and returns a confirmation. However, it lacks details on error handling, permissions, or side effects.

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?

The description is structured with an Args section, making it easy to scan. It is somewhat lengthy but each sentence adds value. The 'User Preferences' line appears outside the description and is not part of the user-facing description.

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 9 parameters and multiple modes, the description covers the main functionality and all parameters. The presence of an output schema means return details are unnecessary. It lacks error handling details, but overall is sufficient for correct usage.

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?

Schema coverage is 0%, so the description must add meaning. It explains each parameter, including formatting (e.g., comma-separated for to/cc/bcc/attachments) and mode values. This compensates well for the lack of schema descriptions.

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 it composes and sends a new email from a specific account. The verb 'compose' and resource 'new email' are specific, and the tool distinguishes itself from sibling tools like reply_to_email or forward_email.

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

Usage Guidelines3/5

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

The description implies usage for composing new emails but does not explicitly contrast with alternatives or provide when-not-to-use guidance. Given the many sibling tools, explicit differentiation would improve clarity.

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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