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Google Business Profile MCP by InsightfulPipe

GMB Prompts

prompts_menu
Read-only

Browse the Google My Business prompt catalog.

  1. request='menu' – List public/system prompts (optionally pass workspace_id + prompt_type).

  2. request='prompt_details' – Fetch prompt body by prompt_id. Set is_custom=True + workspace_id for workspace prompts.

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": {
      "request": "<request>"
    },
    "name": "prompts_menu"
  }
}

Input Schema

NameRequiredDescriptionDefault
requestYes
is_customNo
prompt_idNo
prompt_typeNo
workspace_idNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, so the safety profile is covered. The description adds one genuinely behavioral detail: that workspace prompts require is_custom=True together with workspace_id, a conditional dependency not visible in the annotations. Beyond that it says nothing about what 'menu' returns, pagination, or whether a workspace prompt is invisible without the flag.

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?

Front-loaded with the purpose, then a tight numbered breakdown of the two modes. Every line earns its place; only minor polish (e.g., explicitly tying prompt_id to the prompt_details mode) is missing.

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?

An output schema exists, so return values needn't be described, and the read-only annotation covers safety. The remaining gap is modest: the accepted values for prompt_type and whether the request enum modes require prompt_id are left implicit rather than stated.

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

Parameters4/5

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

Schema description coverage is 0%, so the description must carry parameter meaning, and it touches all five parameters with a stated purpose, including the conditional coupling of is_custom + workspace_id. The gap is prompt_type, whose valid values and semantics are never given, leaving the agent to guess at accepted strings.

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 opens with a specific verb and resource ("Browse the Google My Business prompt catalog") and then enumerates the two discrete operations the tool performs. An agent can distinguish this read-only catalog browse from execute_action/query_data siblings without opening the schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The two request modes are enumerated with the condition that selects each ('menu' for listing, 'prompt_details' for fetching a body), which is clear context for choosing between them. It stops short of stating exclusions or prerequisites, but for a two-mode tool this is adequate routing.

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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