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icloud-mcp

icloud-mcp

by adamzaidi

bulk_delete

Delete multiple iCloud emails at once using filters like sender, domain, date, size, or unread status. Preview changes with a dry run before removing anything.

Instructions

Delete emails matching any combination of filters. Processes in chunks of 500 with per-chunk timeouts for reliability. Use dryRun: true to preview without making changes.

Input Schema

NameRequiredDescriptionDefault
sinceNoOnly emails since this date (YYYY-MM-DD)
beforeNoOnly emails before this date (YYYY-MM-DD)
domainNoMatch any sender from this domain (e.g. substack.com)
dryRunNoIf true, preview what would be deleted without actually deleting
largerNoOnly emails larger than this size in KB
senderNoMatch exact sender email address
unreadNoTrue for unread only, false for read only
accountNoAccount name to use (e.g. 'icloud', 'gmail'). Defaults to first configured account. Use list_accounts to see available accounts.
flaggedNoTrue for flagged only, false for unflagged only
smallerNoOnly emails smaller than this size in KB
subjectNoKeyword to match in subject
hasAttachmentNoOnly emails with attachments (client-side BODYSTRUCTURE scan — must be combined with other filters that narrow results to under 500 emails first)
sourceMailboxNoMailbox to delete from (default INBOX)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.5.1

TDQS

A4.1/5.0
Behavior5/5

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

Crucially, it discloses internal operational mechanics not found in the schema, specifically that it 'Processes in chunks of 500 with per-chunk timeouts for reliability.' This provides the agent with essential information about the tool's execution flow and fault tolerance.

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 highly concise, dedicating minimal space to state the core function, the operational safeguards (chunking/timeouts), and the required safety mechanism (dryRun).

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?

Given the complexity (13 filters) and the lack of output schema, the description is highly complete. It covers how the operation works, how it's secured (dryRun), and how it handles large volumes (chunking/timeouts).

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 coverage is 100%, setting a baseline of 3. The description does not elaborate on the semantics of the 13 specific filters (e.g., how `smaller` interacts with `larger`) beyond stating that they can be used in combination.

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?

The description clearly states the tool deletes emails and emphasizes its ability to process 'any combination of filters,' distinguishing it from simple single-item deletion siblings. It is clear in its function as a bulk deletion utility.

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?

It provides a critical usage guideline by advising the agent to 'Use dryRun: true' when previewing changes. This operational advice is vital for minimizing risk, especially for a tool with high-impact parameters.

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