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Google Workspace MCP Server

Google Workspace MCP Server

by tom275275
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

list_contact_groups

Retrieve contact groups for a specified Google user by providing their email address. Use page size and token to control pagination.

Instructions

List contact groups (labels) for the user.

Args: user_google_email (str): The user's Google email address. Required. page_size (int): Maximum number of groups to return (default: 100, max: 1000). page_token (Optional[str]): Token for pagination.

Returns: str: List of contact groups with their details.

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_contact_groups"
  }
}

Input Schema

NameRequiredDescriptionDefault
page_sizeNo
page_tokenNo
user_google_emailYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.14.3

TDQS

A3.7/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden. It communicates that this is a read/list operation and includes pagination behavior, but it does not disclose authentication requirements, ordering, system-label inclusion, or other behavioral details beyond the basic listing.

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 concise and well-structured, with a clear one-line purpose followed by organized Args and Returns sections. Every section adds useful information and there is no unnecessary fluff.

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 list operation, the description covers the required and optional parameters and the high-level return value. It is mostly complete, but it could be stronger by mentioning when to prefer this over get_contact_group or how authentication relates to user_google_email.

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%, but the description fully compensates by explaining each parameter: user_google_email is required, page_size has default and max limits, and page_token is for pagination. This adds meaning beyond the raw schema types.

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 tool lists contact groups (labels) for a user, using a specific verb and resource. It is clear enough to distinguish from related tools like get_contact_group, though it does not explicitly name or contrast sibling tools.

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?

There is no guidance about when to use this tool versus alternatives such as get_contact_group, manage_contact_group, or list_contacts. The description does not state exclusions, prerequisites, or recommended scenarios.

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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