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Google Tag Manager MCP by InsightfulPipe

by com.insightfulpipe
OverviewDiscussionsAdmin

Google Tag Manager Execute Action

execute_action
Destructive

Execute Google Tag Manager action (Step 3 (FINAL) of workflow).

REQUIRED: Complete these steps first using query_contexts:

  1. request='accounts' - Get workspace_id, brand_id AND available_actions

  2. request='actions_details' with actions=['xxxxxx', 'xxxxxx', 'xxxxxx'] - Get detailed body structure for specific action(s) using actions from available_actions

IMPORTANT: Always call step 2 to see the exact body structure before executing.

Rely on info from steps 1-2 to construct the action body. Follow the schema exactly.

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": {
      "body": "<body>"
    },
    "name": "execute_action"
  }
}

Input Schema

NameRequiredDescriptionDefault
bodyYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare destructiveHint=true, openWorldHint=true, and readOnlyHint=false. The description adds workflow behavior beyond annotations: it is the final step, depends on prior context queries, and requires constructing the body from fetched action details.

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 front-loaded with the execution purpose and numbered prerequisites. It is generally well structured, though the repeated emphasis on calling step 2 is slightly redundant.

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?

Given a destructive, open-world execution tool with a free-form body and an output schema, the description covers the critical prerequisite workflow and where to obtain body details. It could say more about consequences or failure behavior, but annotations already flag destructiveness.

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% and the body is an unconstrained object, so the description cannot rely on structured parameter documentation. It partially compensates by directing the agent to query_contexts 'actions_details' for the exact body structure, but it does not describe any body fields directly.

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 states a specific verb and resource: execute a Google Tag Manager action, and identifies it as the final step of a workflow. It clearly separates execution from the query_contexts prerequisite tools, though the term 'action' remains somewhat generic without examples.

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

Usage Guidelines5/5

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

It explicitly requires completing query_contexts steps first, names the exact request types ('accounts' and 'actions_details'), and states that step 2 must always be called before execution. This gives an agent clear when-to-use and prerequisite guidance.

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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