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google-ecommerce-mcp

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Python
Remote

Merchant Center report query

merchant_report_query
Read-onlyIdempotent

Run Merchant Center reports with MCQL to check product status or free-listing performance and retrieve raw result rows for analysis.

Instructions

Run a Merchant Center report (Merchant API reports:search) with an MCQL query, for example product status or free-listing performance. Returns Google's raw result rows.

Input Schema

NameRequiredDescriptionDefault
queryNoMerchant Center Query Language (MCQL) statement. Tables include product_view (must select id) and product_performance_view (clicks, impressions by date or offer)SELECT id, offer_id, title, aggregated_reporting_context_status FROM product_view LIMIT 50
client_idNoClient id from clients_list. Required when several clients are registered; empty uses the only client (or the environment variables when there is no client registry)

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. Required when several clients are registered; empty uses the only client (or the environment variables when there is no client registry)",
+  "title": "Client Id"
+}
  2. Changed1 schema field changedv0.1.2
    • addedInput schema / properties / query / description
      Added value: +"Merchant Center Query Language (MCQL) statement. Tables include product_view (must select id) and product_performance_view (clicks, impressions by date or offer)"
  3. First observedv0.1.0

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false, and openWorldHint, so the safety profile is covered. The description adds one genuinely useful behavioral fact — that results are Google's raw, unprocessed rows — but says nothing about pagination, row limits, quota, or how errors surface for an open-world query tool.

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?

Two tight sentences with the action front-loaded and the return behavior appended; no filler. The parenthetical API reference is arguably redundant, keeping it just short of ideal.

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?

With no output schema, the description does note the return shape ('raw result rows') and the schema fully documents both parameters, so an agent has enough to invoke it. Missing operational details (limits, pagination, failure modes) are the only 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%, and the schema already documents the MCQL statement, available tables, and the client_id sourcing/requirement rules. The description adds no parameter-level detail beyond restating the MCQL query concept, so the baseline 3 applies.

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 ('Run a Merchant Center report ... with an MCQL query') and gives concrete example use cases (product status, free-listing performance). It does not explicitly distinguish itself from adjacent read tools such as merchant_products or gads_query, but the MCQL/reports:search framing makes the capability identifiable.

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 examples hint at when the tool applies, but there is no explicit when-to-use/when-not guidance and no mention of the sibling alternatives (e.g. merchant_products for simple product listing vs this for arbitrary MCQL reporting). Usage is implied rather than stated.

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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