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Google Workspace MCP Server

Google Workspace MCP Server

by tom275275
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

list_script_processes

Get a list of recent execution processes for a user's Apps Scripts. Filter by script ID and page size to track and audit script runs.

Instructions

Lists recent execution processes for user's scripts.

Args: service: Injected Google API service client user_google_email: User's email address page_size: Number of results (default: 50) script_id: Optional filter by script ID

Returns: str: Formatted string with process list

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>"
    },
    "name": "list_script_processes"
  }
}

Input Schema

NameRequiredDescriptionDefault
page_sizeNo
script_idNo
user_google_emailYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.14.3

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations, the description carries the transparency burden. It does convey a non-mutating read operation ('Lists') and mentions the return type ('Formatted string'), but it does not disclose side effects, auth requirements, or how 'recent' is determined.

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?

The description is front-loaded with a clear one-sentence purpose, then organized into Args and Returns sections. There is no filler or redundant elaboration.

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 covers purpose, parameters, and return value, and an output schema exists. However, it lacks guidance on when to use this tool versus the many script-related siblings, and it does not fully resolve how the injected 'service' argument relates to the declared request schema.

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?

Schema coverage is 0%, so the description's Args section is important. It names all three schema parameters and gives brief glosses, though most add little beyond what the schema already shows. The mention of 'service' is helpful context, but it does not clarify that this is an injected runtime client, not a user-supplied request field.

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 and resource: 'Lists recent execution processes for user's scripts.' This clearly distinguishes the tool from siblings like list_script_projects or get_script_metrics, since 'execution processes' is a unique scope.

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 gives no guidance on when to choose this tool over related script tools such as list_script_projects or get_script_metrics, and it does not mention exclusions or prerequisites. Usage is only implied by the stated purpose.

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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