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isityael

Apple Mail MCP Server

by isityael

get_newsletters

Detect newsletter and digest emails from your Apple Mail accounts by common patterns. Filter by account, days back, and max results.

Instructions

Find newsletter and digest emails by detecting common patterns. Automatically identifies emails from newsletter services and digest senders.

Args: account: Account to search. If None, searches all accounts. days_back: Only search last N days (default: 7) max_results: Maximum newsletters to return (default: 25) include_content: Include content preview (default: True) max_content_length: Max preview length (default: 500)

Returns: List of detected newsletter emails sorted by date

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

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
accountNo
days_backNo
max_resultsNo
include_contentNo
max_content_lengthNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations provided, so the description carries full burden. It states 'automatically identifies' but does not disclose how detection works, whether it modifies email state, or any limitations (e.g., only works on certain mailboxes).

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 well-structured with Args and Returns sections, clear and organized. It is concise enough to convey essential information without unnecessary fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With an output schema present, return value details are covered. However, the description lacks context on prerequisites (e.g., account authentication) and behavioral constraints. Adequate but with gaps.

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%, but the description provides detailed docstrings for each parameter (account, days_back, max_results, include_content, max_content_length), adding meaning beyond the schema's types and defaults.

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 'finds newsletter and digest emails by detecting common patterns', using a specific verb and resource. It distinguishes itself from siblings like search_emails by focusing on newsletters.

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?

No guidance on when to use this tool versus alternatives (e.g., search_emails, get_recent_emails). The description does not mention when not to use it or any prerequisites.

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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