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tom275275

Google Workspace MCP Server

by tom275275

search_contacts

Find contacts in Google Workspace by name, email, or phone number. Returns matching people with their basic information to help you locate the right person.

Instructions

Search contacts by name, email, phone number, or other fields.

Args: user_google_email (str): The user's Google email address. Required. query (str): Search query string (searches names, emails, phone numbers). page_size (int): Maximum number of results to return (default: 30, max: 30).

Returns: str: Matching contacts with their basic information.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
page_sizeNo
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?

No annotations are provided, so the description carries the disclosure burden. It explains matching behavior, the return type, and the page_size cap of 30. It does not explicitly state that this is read-only or that authentication must already exist, but the verb 'search' makes the non-mutating intent reasonably clear.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The summary is front-loaded and the Args/Returns structure is easy to scan. There is minor redundancy between 'name, email, phone number' in the summary and 'searches names, emails, phone numbers' in the query parameter description, but it is still concise and useful.

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 low-complexity search tool, the description covers the required user identifier, query semantics, and result limit. It could add a note about when to prefer list_contacts or whether the returned string is plain text or JSON, but these are minor gaps, and an output schema exists.

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?

The input schema has 0% description coverage, so the description fully compensates by documenting all three parameters: user_google_email (required), query (searchable fields), and page_size (default and max). This adds real meaning beyond what the schema 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 states a specific verb ('Search'), a resource ('contacts'), and searchable fields ('name, email, phone number, or other fields'). This clearly distinguishes it from sibling tools like list_contacts and get_contact.

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 intended use is implied: use this when you need to find contacts by a query rather than listing all contacts or retrieving a specific contact by ID. However, it never explicitly names alternatives or states when not to use this tool, so the agent must infer the boundary.

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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