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Leonamin

Naver Mail MCP Server

by Leonamin

mark_mails_unread

Change selected emails back to unread status in your Naver Mail account to mark messages for later review or follow-up.

Instructions

메일을 읽지 않음 상태로 변경

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
mail_uidsYes읽지 않음 처리할 메일들의 UID 목록

Implementation Reference

  • The core logic that marks emails as unread by flagging them in the mailbox.
    def mark_as_unread(self, mail_uids: List[str]) -> None:
        """
        메일을 읽지 않음 상태로 변경합니다.
        """
        with self._get_mailbox_client() as mailbox:
            mailbox.flag(mail_uids, '\\Seen', False)
  • server.py:224-237 (registration)
    MCP tool definition/registration for mark_mails_unread.
    Tool(
        name="mark_mails_unread",
        description="메일을 읽지 않음 상태로 변경",
        inputSchema={
            "type": "object",
            "properties": {
                "mail_uids": {
                    "type": "array",
                    "items": {"type": "string"},
                    "description": "읽지 않음 처리할 메일들의 UID 목록"
                }
            },
            "required": ["mail_uids"],
        }
  • The handler block in server.py that processes the mark_mails_unread tool request.
    elif name == "mark_mails_unread":
        mail_uids = args.get("mail_uids", [])
    
        if not mail_uids:
            return [TextContent(type="text", text="읽지 않음 처리할 메일 UID 목록이 필요합니다.")]
    
        mail_service.mark_as_unread(mail_uids)
        return [TextContent(type="text", text=f"{len(mail_uids)}개의 메일이 읽지 않음 상태로 변경되었습니다.")]
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the action ('change to unread status') but lacks details on permissions required, whether the change is reversible, side effects (e.g., updating timestamps), error handling, or response format. For a mutation tool with zero annotation coverage, this is a significant gap in transparency.

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 a single, efficient sentence in Korean that directly states the tool's purpose without unnecessary words. It is front-loaded with the core action, making it easy to parse quickly, and every part of the sentence contributes essential information.

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

Completeness2/5

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

Given the tool's complexity as a mutation operation with no annotations and no output schema, the description is incomplete. It lacks details on behavioral aspects (e.g., what happens on success/failure), usage context, and return values, leaving gaps that could hinder an AI agent's ability to invoke it correctly without additional assumptions.

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?

Schema description coverage is 100%, with the parameter 'mail_uids' clearly documented in the schema as '읽지 않음 처리할 메일들의 UID 목록' (list of UIDs of emails to mark as unread). The description adds no additional meaning beyond this, such as format examples or constraints, so it meets the baseline for high schema coverage without compensating value.

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 action ('메일을 읽지 않음 상태로 변경' translates to 'Change emails to unread status') and identifies the resource (emails). It distinguishes from siblings like 'mark_mails_read' by specifying the opposite state, though it doesn't explicitly contrast with other tools like 'mark_mails_important' or 'delete_mails' beyond the implied state change.

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 is provided on when to use this tool versus alternatives. The description does not mention prerequisites (e.g., needing valid mail UIDs), exclusions (e.g., not applicable to already unread mails), or contextual cues (e.g., use for marking emails as unread after accidental reads). It relies solely on the tool name for differentiation.

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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