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google-data-mcp

google-data-mcp

by seliem-attia

GTM: Tags/triggers/variables in the workspace

gtm_list_entities
Read-only

Retrieves complete JSON objects, including parameters and fingerprints, for a Google Tag Manager entity type in a workspace to inspect or prepare changes via gtm_save_entity.

Instructions

Returns the complete JSON objects (incl. parameter, fingerprint) of an entity type in the workspace — template for changing via gtm_save_entity.

Input Schema

NameRequiredDescriptionDefault
accountIdYesGTM accountId (from gtm_list_accounts)
entityTypeYesEntity type: tags, triggers, variables, folders, templates, clients, transformations, zones
containerIdYesGTM containerId, numeric
workspaceIdYesWorkspace ID (from gtm_list_workspaces / gtm_create_workspace)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.6.1

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds real value beyond that by disclosing the shape of the payload — complete JSON objects including parameters and fingerprint — which matters for the save round-trip. It omits volume/pagination behavior, keeping it from a 5.

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?

A single front-loaded sentence with no filler; the payload description and the downstream save hint both earn their place. Nothing is repeated from the title or schema.

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?

For a read-only list tool with fully documented required params and no output schema, the description says enough about what comes back to be actionable. A note on result volume or whether all entities of a type are returned would close the remaining gap.

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 description coverage is 100%, with all four required parameters documented and the entityType enum spelled out, so the schema carries parameter meaning. The description adds no syntax, ID-chaining, or enum detail beyond what is already structured, which is the baseline-3 case.

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?

States a specific verb and resource: returns the complete JSON objects of an entity type in a workspace, and the title enumerates tags/triggers/variables. It also positions itself relative to gtm_save_entity. It does not distinguish itself from adjacent read tools like gtm_export_workspace or gtm_list_workspaces, so a 4 rather than 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 Guidelines3/5

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

The phrase 'template for changing via gtm_save_entity' implies the read-then-modify workflow, which is useful context. However, it gives no explicit when-not guidance and does not say how this differs from gtm_export_workspace or gtm_sync_workspace, leaving the agent to infer the boundary.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.