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thrix

gcloud-workspace-mcp

by thrix

gmail_get_message

Read-only

Fetch a single Gmail message by ID to read its headers, decoded body, or attachments; supports text, metadata, or raw .eml formats.

Instructions

Fetch a single Gmail message.

Uses ADC credentials and sends the mandatory quota-project header.

Args: message_id: The Gmail message id. format: "text" (default) returns {id, threadId, labelIds, headers, body, attachments} with the body decoded to plain text (HTML-only mail is stripped of tags). "metadata", "minimal" and "full" return the Gmail message resource unchanged, up to 1 MB. "raw" saves the whole RFC 822 message, attachments included, to <message id>.eml in the download directory, and returns the resource with path, mimeType and bytes in place of the base64 raw field.

Returns: The message as JSON.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
formatNotext
message_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.6/5.0
Behavior5/5

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

Annotations only cover readOnlyHint/openWorldHint, and the description adds substantial behavior the annotations cannot: ADC credential usage, the mandatory quota-project header, the 1 MB cap on metadata/minimal/full, HTML tag-stripping on text format, and the side effect that 'raw' writes an .eml file to the download directory and swaps the base64 raw field for path/mimeType/bytes.

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?

Front-loads the one-line purpose, then uses standard Args/Returns sections with no filler. Every clause (decoding, size cap, file write, field substitution) conveys information an agent needs to pick a format correctly.

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

Completeness5/5

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

An output schema exists, yet the description still explains the divergent return shapes per format, which is exactly the detail that matters given the format-dependent responses. Nothing needed to invoke the tool correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description carries the full burden and does: message_id is identified as the Gmail message id, and all four format values are enumerated with their distinct return shapes and defaults. This is far beyond anything the bare schema conveys.

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?

States a specific verb and resource ('Fetch a single Gmail message'), which cleanly separates it from gmail_search (bulk) and gmail_get_thread (thread-level). An agent can identify the tool from the first line alone.

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 format modes are well explained, which effectively guides parameter selection, but the description never states when to prefer this tool over gmail_search or gmail_get_thread, nor any prerequisites for calling it. Usage is implied by the resource name rather than declared.

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