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ai-zerolab

MCP Email Server

by ai-zerolab

list_emails_metadata

Retrieve email metadata (subject, sender, recipients, date) with filters like sender, recipient, date range, read status, and attachments. Use returned email IDs to fetch full content.

Instructions

List email metadata (email_id, subject, sender, recipients, date) without body content. Returns email_id for use with get_emails_content.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyNoSearch for text in the email body (IMAP BODY).
pageNoThe page number to retrieve (starting from 1).
seenNoFilter by read status: True=read, False=unread, None=all.
textNoSearch for text in the entire message — headers and body (IMAP TEXT).
orderNoOrder emails by field. `asc` or `desc`.desc
sinceNoRetrieve emails since this datetime (UTC).
beforeNoRetrieve emails before this datetime (UTC).
flaggedNoFilter by flagged/starred status: True=flagged, False=unflagged, None=all.
mailboxNoThe mailbox to search.INBOX
subjectNoFilter emails by subject.
answeredNoFilter by replied status: True=replied, False=not replied, None=all.
page_sizeNoThe number of emails to retrieve per page.
to_addressNoFilter emails by recipient address.
account_nameYesThe name of the email account.
from_addressNoFilter emails by sender address.
has_attachmentNoFilter by attachment presence: True=has attachment, False=none, None=all (multipart/mixed heuristic; may miss inline images or yield false positives).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageYes
sinceYes
totalYes
beforeYes
emailsYes
subjectYes
page_sizeYes
Behavior3/5

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

With no annotations, the description carries full burden. It correctly states the tool retrieves metadata without body content and returns email_id for further use. However, it omits important behavioral details such as pagination, sorting, rate limits, or idempotency, which are left to the schema. Some users may need more context.

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 extremely concise: two sentences that front-load the essential purpose and key output. Every sentence adds value with no wasted words.

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 (16 parameters, no annotations, output schema present), the description adequately covers the core purpose and links to a sibling tool. The output schema handles return value details. However, it could provide more context on how filters combine or pagination behavior.

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 has full coverage (100% of parameters have descriptions), so the baseline is 3. The description adds context about the output fields but does not enhance understanding of the parameter semantics beyond what the schema already provides.

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 verb 'list', the resource 'email metadata', and specifies the fields returned (email_id, subject, sender, recipients, date) without body content. It distinguishes itself from the sibling 'get_emails_content' by noting that the returned email_id can be used with that tool.

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?

The description provides implicit guidance by contrasting with get_emails_content ('without body content... for use with get_emails_content'), indicating when to use this tool (to get metadata) and when to use the sibling (to get content). However, it does not explicitly exclude other scenarios or mention alternative tools for different filtering needs.

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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