google-workspace-mcp

contacts_search

Search Google Workspace contacts by name, email, or phone number to retrieve matching contact details.

Instructions

Search contacts by name, email, or phone number.

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": {
      "query": "<query>"
    },
    "name": "contacts_search"
  }
}

Input Schema

Name	Required	Description	Default
`query`	Yes
`max_results`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Aug 2, 2026

TDQS

B3.1/5.0

Behavior2/5

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

With no annotations, the description carries the full burden for behavioral disclosure. It only states the search criteria and omits details about result format, pagination, case sensitivity, or how multiple fields are combined. The max_results parameter is not mentioned in the description, leaving the agent guessing about result limits.

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?

A single, front-loaded sentence that succinctly conveys the tool's purpose without unnecessary words. It is appropriately sized for a simple search operation.

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

Completeness3/5

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

The description gives the essential purpose and query semantics, and the output schema covers return values. However, it lacks usage guidelines and behavioral details, and with no annotations, the sparse description leaves notable gaps for an AI agent to fully understand the tool's invocation and expected behavior.

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

Parameters3/5

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

The description adds meaning to the 'query' parameter by specifying it matches name, email, or phone number, which goes beyond the bare schema label. However, it does not explain the 'max_results' parameter, leaving a gap for one of the two parameters in a schema with 0% description coverage.

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 searches contacts by name, email, or phone number, using a specific verb and resource with search criteria. However, it does not explicitly differentiate from sibling tools like contacts_list, which could also serve a similar lookup purpose.

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?

No guidance is provided on when to use this tool versus alternatives like contacts_list or when not to use it. There are no explicit exclusions or recommended contexts.

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

Deploy Server