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tom275275

Google Workspace MCP Server

by tom275275

get_gmail_attachment_content

Download a Gmail attachment by supplying message and attachment IDs. Get a local file path or temporary download URL to access the content.

Instructions

Downloads an email attachment and saves it to local disk.

In stdio mode, returns the local file path for direct access. In HTTP mode, returns a temporary download URL (valid for 1 hour). May re-fetch message metadata to resolve filename and MIME type.

Args: message_id (str): The ID of the Gmail message containing the attachment. attachment_id (str): The ID of the attachment to download. user_google_email (str): The user's Google email address. Required.

Returns: str: Attachment metadata with either a local file path or download URL.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
message_idYes
attachment_idYes
user_google_emailYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.14.3

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden and does a good job: it discloses that the tool writes to local disk, returns different response types by mode, that the HTTP URL is temporary (valid for 1 hour), and that metadata may be re-fetched. This is meaningful behavioral context beyond the name and schema.

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 front-loaded with the core action, then provides mode-specific behavior, parameter semantics, and return type. Every sentence earns its place without unnecessary filler, and the structure is easy to scan.

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 simple three-parameter Gmail attachment download tool, the description covers the essential context: what it does, return behavior by mode, and parameter meanings. It does not cover error cases or explicit auth prerequisites, but these are not critical for this straightforward operation.

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 description coverage is 0%, but the description provides a clear Args section explaining the role of each parameter: message_id identifies the containing message, attachment_id identifies the attachment, and user_google_email supplies the user's address. This compensates well for the schema's lack of parameter 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 a specific verb ('Downloads') and resource ('an email attachment') and explains the resulting behavior: saving to local disk and returning a path or URL. This distinguishes it from related sibling tools like get_gmail_message_content and download_chat_attachment.

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 explains behavior in stdio vs HTTP mode, which helps an agent know what to expect, but it does not explicitly state when to use this tool over alternatives or when not to use it. Usage context is implied by the tool's purpose rather than explicitly guided.

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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