Skip to main content
Glama
Sign In

Google Tag Manager MCP by InsightfulPipe

by com.insightfulpipe
OverviewDiscussionsAdmin

Server Details

Hosted Google Tag Manager MCP server, with each action switched on or off per account.

Ownership verified
Status
Healthy
Uptime
100.0% over the last 24 hours
OAuth
Works in Glama
Last Tested
Transport
Streamable HTTP · MCP 2025-11-25
URL
Repository
Insightful-Pipe/google-tag-manager-mcp-server
GitHub Stars
0
ChatGPT
–
Claude
–

TDQS

A3.8/5.0

Scored across 4 tools

Disambiguation2/5

execute_action and query_data are nearly indistinguishable: both are described as 'Step 3 (FINAL)' of the same workflow, both require the same query_contexts steps, and both say 'follow the schema exactly.' Only the words 'action' versus 'query' hint at a boundary, which is too subtle to prevent misselection.

Naming Consistency3/5

All names use snake_case, but the pattern is mixed: query_contexts, query_data, and execute_action are verb_noun while prompts_menu is noun_noun with reversed order. It is readable, but not a predictable convention throughout.

Tool Count4/5

Four tools is a reasonable, well-scoped set for a generic action-dispatch server: metadata/context lookup, data querying, action execution, and prompt browsing. The count is not excessive, though the thin separation between query_data and execute_action makes the set feel smaller than it should.

Completeness3/5

The generic execute_action/query_data pattern may cover arbitrary GTM operations, but the surface does not explicitly expose core GTM lifecycles (accounts, containers, workspaces, tags, triggers, variables, versions). The presence of metadata and prompts helps, but agents must discover operations dynamically rather than through a complete visible tool surface.

Available Tools

4 tools
execute_actionGoogle Tag Manager Execute ActionA
Destructive
Inspect

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.

Inputs: body (required). Returns: object

prompts_menuGoogle Tag Manager PromptsA
Read-only
Inspect

Browse the Google Tag Manager 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.

Inputs: request (required), is_custom, prompt_id, prompt_type, +1 more. Returns: object

query_contextsGoogle Tag Manager Setup HelperA
Read-only
Inspect

Helper for planning InsightfulPipe Google Tag Manager data queries.

Step 1: request='accounts' – Retrieve workspace_id, brand_id, other source metadata, AND available_actions (all tables you can query).

Step 2: request='actions_details' with actions=['xxxxxx', 'xxxxxx', 'xxxxxx'] – REQUIRED before querying. Replace with actions from available_actions to get the exact request body, required identifiers, fields, time ranges, and notes for each action.

Optional: request='available_actions' – Standalone call to list all available tables/actions (already included in accounts response).

Optional: request='brands' with brand_id + workspace_id to pull brand guidelines.

Inputs: request (required), actions, brand_id, platform, +1 more. Returns: object

query_dataGoogle Tag Manager Data QueryA
Read-only
Inspect

Query Google Tag Manager data (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 querying.

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

Inputs: body (required). Returns: object

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

    Related MCP Connectors

    Related MCP Servers

    • mcp-tagmanager

      gustavomkt
      F
      license
      Not graded
      quality
      D
      maintenance
      MCP server for Google Tag Manager, offering tools to manage accounts, containers, workspaces, tags, triggers, and versions, with explicit confirmation for production-affecting actions.
      -

    • mcp-gtm-ga4

      mharnett
      A
      license
      A
      quality
      B
      maintenance
      MCP server for Google Tag Manager and GA4, enabling tag management, consent auditing, workspace versioning, and analytics reporting through natural language.
      11
      71 npm
      3
      MIT

    • @ainative/gtm-mcp

      AINative-Studio
      A
      license
      Not graded
      quality
      C
      maintenance
      MCP server for Google Tag Manager and Google Ads, enabling AI agents to audit, fix, and manage GTM containers and Google Ads campaigns programmatically.
      64 npm
      MIT

    • GTM MCP Server

      pouyanafisi
      A
      license
      Not graded
      quality
      C
      maintenance
      MCP server for Google Tag Manager API v2, enabling programmatic management of accounts, containers, workspaces, tags, triggers, variables, and version workflows.
      37 npm
      15
      MIT
    Try in Browser
    Claude Code, inside the Godot 4 editorFlockbay puts an AI agent in the real Godot 4 editor: it writes GDScript, runs your game and fixes what breaks. Free, or bring your own Claude Code or Codex.flockbay.comAd

    Glama MCP Gateway

    Add one secure layer between your agents and this server.

    Resources