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google-ecommerce-mcp

by MoonEyes
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

Google Ads accounts

gads_accounts
Read-onlyIdempotent

List Google Ads customer accounts the token can access to choose a customer_id for performance or query tools. Returns configured and login customer IDs with cached discovery.

Instructions

Google Ads customer accounts the Google Ads token can read directly (customers:listAccessibleCustomers), with the configured customer (GADS_CUSTOMER_ID, or the client's) and login customer (manager account), to pick a customer_id for gads_performance or gads_query. Returns {"customers": [{"id"}], "configured_customer_id", "login_customer_id", "cached"} (cached: true when the list comes from the 5-minute discovery cache). With a client registry only the client's own customers are listed ("hidden_customers" counts the others).

Input Schema

NameRequiredDescriptionDefault
client_idNoClient id from clients_list; empty uses the only client

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.5.0
    • addedInput schema / properties / client_id
      Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "description": "Client id from clients_list; empty uses the only client",
+  "title": "Client Id"
+}
  2. Addedv0.4.0

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already cover readOnly/idempotent/non-destructive, but the description adds real behavioral context: results may come from a 5-minute discovery cache (cached: true), the configured vs. login customer distinction, and hidden_customers counting suppressed accounts. It stops short of auth/rate-limit caveats but goes well beyond the annotation set.

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-loads the core purpose and return shape, then layers the client-registry nuance. The second sentence is dense and parenthetical-heavy, but nearly every clause carries information an agent needs.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description compensates by spelling out the return payload keys (customers[].id, configured_customer_id, login_customer_id, cached). Combined with the client-scoping note, an agent has everything needed to call and interpret this tool.

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 coverage is 100% and the schema already explains that client_id comes from clients_list and empty falls back to the only client. The description adds value by explaining the consequence of client scoping (only the client's own customers are listed), which meaningfully extends the parameter's behavior.

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?

States a specific verb+resource: lists Google Ads customer accounts the token can read directly, naming the underlying API call (customers:listAccessibleCustomers). It also positions itself against siblings gads_performance and gads_query as the source of a customer_id for those tools.

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?

Explicitly says to use the result to pick a customer_id for gads_performance or gads_query, and explains the client-registry scoping case. It gives clear context for when this tool is the right one, though it does not state an explicit exclusion or when-not-to-use case.

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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