google-workspace-mcp-advanced

send_message

Send messages to Google Chat spaces with optional thread replies and dry run mode to preview before sending.

Instructions

Sends a message to a Google Chat space.

Args: dry_run (bool): If True, preview the message send without mutating Chat.

Returns: str: Confirmation message with sent message 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>",
      "space_id": "<space_id>",
      "message_text": "<message_text>"
    },
    "name": "send_message"
  }
}

Input Schema

Name	Required	Description	Default
`user_google_email`	Yes
`space_id`	Yes
`message_text`	Yes
`thread_key`	No
`dry_run`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.10Jun 2, 2026

TDQS

C2.7/5.0

Behavior3/5

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

Annotations are absent, so the description carries the full burden. It discloses the 'dry_run' parameter behavior ('preview without mutating') and states the return type. However, it omits details like authentication requirements, error handling, or rate limits. The dry_run disclosure adds value but not comprehensively.

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 very short, with a single sentence of purpose plus an Args and Returns section. It is concise but could use a bit more structure, e.g., a clear one-liner followed by parameter details. However, it is not overly verbose.

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?

Given the tool has 5 parameters with 3 required, and no parameter descriptions in the schema, the description is incomplete. It covers only one parameter and provides a vague return description. With sibling complexity, it lacks enough context for correct invocation.

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

Parameters1/5

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

Schema description coverage is 0%, so the description must explain parameters. Only 'dry_run' is described. Required parameters 'user_google_email', 'space_id', and 'message_text' are completely undocumented. 'thread_key' is also omitted. This is a critical gap.

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 'Sends a message to a Google Chat space,' which specifies the verb and resource. However, it does not differentiate from sibling tools like 'send_gmail_message' or 'draft_gmail_message', which have different targets or verb forms. A score of 4 reflects clarity but lack of sibling differentiation.

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?

The description provides no guidance on when to use this tool versus alternatives. It does not mention scenarios when send_gmail_message or other messaging tools should be preferred. No explicit when-to-use or when-not-to-use context is given.

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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