google-workspace-mcp-advanced

list_gmail_labels

Lists all Gmail labels for a specified user, returning each label's ID, name, and type.

Instructions

Lists all labels in the user's Gmail account.

Args: user_google_email (str): The user's Google email address. Required.

Returns: str: A formatted list of all labels with their IDs, names, and types.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "user_google_email": "<user_google_email>"
    },
    "name": "list_gmail_labels"
  }
}

Input Schema

Name	Required	Description	Default
`user_google_email`	Yes

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.10Jun 2, 2026

TDQS

A4/5.0

Behavior3/5

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

No annotations are provided, so the description carries the transparency burden. It discloses the return format (formatted list with IDs, names, and types) and the required argument, but it does not explicitly state auth requirements or confirm read-only behavior, though 'Lists' implies it.

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 compact and well-structured: one purpose sentence followed by Args and Returns sections. Every sentence adds value with no redundancy or filler.

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?

The tool is a simple read-only listing operation, and the description gives the core purpose, required input, and return contents. It is sufficient for correct invocation, though it could briefly mention auth prerequisites or clarify that it returns all labels without filtering.

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?

The single parameter user_google_email is explained as 'The user's Google email address' and marked Required, adding meaning beyond the bare schema type. Since there is only one parameter, this fully covers the parameter surface, though it offers no advanced format details.

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 uses the specific verb 'Lists' and names the resource 'all labels in the user's Gmail account,' clearly distinguishing it from sibling tools like list_gmail_filters and manage_gmail_label. The purpose is immediately unambiguous.

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 gives no explicit when-to-use guidance or alternatives, but the verb and resource make the intended use apparent. It does not mention cases where a different Gmail label-related tool would be more appropriate.

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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