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tom275275

Google Workspace MCP Server

by tom275275

search_messages

Locate Google Chat messages by text query using a user's Google email. Narrow results to a specific space with space ID and control page size to get formatted matching messages.

Instructions

Searches for messages in Google Chat spaces by text content.

Returns: str: A formatted list of messages matching the search query.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
space_idNo
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

C2.7/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only states that a formatted list of matches is returned; it does not disclose authentication requirements, pagination behavior, the effect of the optional space_id, or whether search is limited to the authenticated user's accessible spaces. For a search tool with no annotation coverage, key behavioral traits are missing.

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 description is short and front-loaded, with the core purpose stated in the first sentence and the return type in the second. There is no filler or repetition. However, the returned type line adds little value beyond the output schema and might have been better used for behavioral or parameter details.

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

Completeness2/5

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

For a tool with 4 parameters, no annotations, and an output schema, the description is too sparse to fully guide an agent. It omits prerequisites (e.g., authentication), the meaning of optional parameters, pagination behavior, and how results are ordered or scoped. The output schema covers return values partially, but the absence of usage context makes the definition incomplete.

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

Parameters2/5

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

The schema has 0% description coverage and the tool description adds no parameter-specific meaning. While 'by text content' hints at the query parameter, the roles of space_id, page_size, and user_google_email are not explained. Parameter names and defaults provide some self-evidence, but the description does not compensate for the complete lack of schema descriptions.

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 operation ('Searches for messages'), the resource scope ('in Google Chat spaces'), and the method ('by text content'). It distinguishes itself from Gmail search siblings by explicitly naming Google Chat spaces, and from get_messages which implies listing rather than searching. However, it does not explicitly contrast with any sibling tool, so it falls slightly short of a 5.

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 on when to use this tool versus alternatives such as get_messages, search_gmail_messages, or list_spaces. No scenarios, prerequisites (like start_google_auth), or exclusions are provided. The usage context is only implicit in the name and description, which is insufficient.

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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