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MoonEyes

google-ecommerce-mcp

by MoonEyes
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

Ads overview (all platforms)

ads_overview
Read-onlyIdempotent

Compare Google, Meta, and OpenAI Ads totals side by side for one client and date range: spend, impressions, clicks, conversions, conversion value, and ROAS.

Instructions

Google Ads, Meta and OpenAI Ads totals side by side for one period: spend, impressions, clicks, conversions and conversion value as reported by each platform, the platform's own ROAS, currency, attribution windows and date range. A platform not configured or failing gets its own block without blocking the others (partial). combined adds spends only when every currency is the same (else null with combined_reason; a platform without activity adds zeros and needs no currency) and computes ROAS as total value / total spend. Conversions overlap between platforms: their sum is not deduplicated (warning). Multi-client: one client only (client_id), and only the platforms that client has; never two clients mixed.

Input Schema

NameRequiredDescriptionDefault
end_dateYesLast day, YYYY-MM-DD, on or after start_date
client_idNoClient id from clients_list; empty uses the only client. Only that client's platforms are added up
start_dateYesFirst day, YYYY-MM-DD (each platform counts in its own account timezone)

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. Only that client's platforms are added up",
+  "title": "Client Id"
+}
  2. Addedv0.4.0

TDQS

A4.4/5.0
Behavior5/5

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

Annotations already cover read-only/idempotent safety, but the description goes far beyond them: failing or unconfigured platforms are isolated into their own block (partial), combined spend is null unless all currencies match with a combined_reason, ROAS is defined as total value / total spend, and cross-platform conversions overlap are explicitly not deduplicated. These are real behavioral traits an agent could not infer otherwise.

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-loaded with the core purpose before the caveats, and nearly every clause carries distinct information. The long run-on sentences with stacked parentheses (combined_reason, currency rules, overlap warning) make it dense and harder to scan than it needs to be.

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 carries the full burden and does so: it names the returned metrics, explains the partial per-platform block structure, the combined aggregation and null semantics, and the cross-platform overlap caveat. Nothing essential for correct interpretation is missing.

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%, so the schema already documents start_date, end_date and client_id (including the empty-uses-only-client and per-platform timezone details). The description largely restates that scoping, adding only the 'never two clients mixed' constraint, which is marginal added value at this coverage level.

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 concrete verb and resource – pull Google Ads, Meta and OpenAI Ads totals side by side for one period – and enumerates the exact metrics returned (spend, impressions, clicks, conversions, conversion value, ROAS, currency, attribution windows, date range). This is clearly distinguishable from the single-platform siblings like gads_query, meta_insights and openai_ads_insights.

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?

The cross-platform scope and the 'one client only (client_id)' rule establish when this tool is the right choice, and the partial-failure note explains what happens when a platform is misconfigured. However, no sibling is named as an alternative and there is no explicit when-not-to-use guidance (e.g. use gads_query for per-campaign breakdowns).

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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