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Python
Hybrid

google_ads_device_analyze

Compare Google Ads campaign performance across desktop, mobile, and tablet to identify spend with zero conversions and device-level CPA or CTR gaps.

Instructions

Compare Google Ads campaign performance across device segments (Desktop / Mobile / Tablet). Returns {campaign_id, campaign_name, period, devices:[{device_type, impressions, clicks, cost, conversions, ctr (percent), average_cpc, cpa, cvr (percent)}], insights:[strings]}, sorted by cost descending. cpa is None when conversions == 0. Insights fire for devices with spend and zero conversions, worst/best CPA ratios > 1.5x, and Mobile CTR less than half of Desktop CTR. Read-only. Returns a 'message' field and empty devices list when no device-segmented data exists. For applying device bid modifiers use google_ads_bid_adjustments_update or google_ads_device_targeting_set; for the raw ad-schedule criteria (hour-of-day targeting config, NOT performance segmentation by hour) use google_ads_schedule_targeting_list.

Input Schema

NameRequiredDescriptionDefault
periodNoReporting window for the metrics. Default 'LAST_30_DAYS'. Use a shorter window (LAST_7_DAYS / LAST_14_DAYS) when diagnosing recent changes; use LAST_90_DAYS for trend baselines. Also accepts an explicit range — "YYYY-MM-DD..YYYY-MM-DD" (the spelling Meta Ads takes too) or, in GAQL spelling, "BETWEEN 'YYYY-MM-DD' AND 'YYYY-MM-DD'" — both endpoints inclusive, in the account's time zone, for a window no trailing constant can reach (e.g. a single past calendar month). One asymmetry to know about: every constant except LAST_90_DAYS is resolved by Google Ads in the account's reporting time zone, whereas LAST_90_DAYS has no API constant and is expanded by mureo into the 90 days ending yesterday **on the server's date**, so its edges can differ by a day when the server and the account are in different zones. Pass an explicit range when the exact boundary matters.
campaign_idYesCampaign ID as a numeric string without dashes (e.g. '23743184133'). Obtain via google_ads_campaigns_list.
customer_idNoGoogle Ads customer ID as a 10-digit string without dashes (e.g. '1234567890'). Optional — falls back to GOOGLE_ADS_CUSTOMER_ID / GOOGLE_ADS_LOGIN_CUSTOMER_ID from the configured credentials when omitted.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv0.33.0
    • changedInput schema / properties / period / anyOf
      Previous value: -[
-  {
-    "enum": [
-      "TODAY",
-      "YESTERDAY",
-      "THIS_WEEK_SUN_TODAY",
-      "THIS_WEEK_MON_TODAY",
-      "LAST_BUSINESS_WEEK",
-      "LAST_WEEK_SUN_SAT",
-      "LAST_WEEK_MON_SUN",
-      "LAST_7_DAYS",
-      "LAST_14_DAYS",
-      "LAST_30_DAYS",
-      "LAST_90_DAYS",
-      "THIS_MONTH",
-      "LAST_MONTH"
-    ],
-    "type": "string"
-  },
-  {
-    "pattern": "\\ABETWEEN '([0-9]{4}-[0-9]{2}-[0-9]{2})' AND '([0-9]{4}-[0-9]{2}-[0-9]{2})'\\Z",
-    "type": "string"
-  }
-]New value: +[
+  {
+    "enum": [
+      "TODAY",
+      "YESTERDAY",
+      "THIS_WEEK_SUN_TODAY",
+      "THIS_WEEK_MON_TODAY",
+      "LAST_BUSINESS_WEEK",
+      "LAST_WEEK_SUN_SAT",
+      "LAST_WEEK_MON_SUN",
+      "LAST_7_DAYS",
+      "LAST_14_DAYS",
+      "LAST_30_DAYS",
+      "LAST_90_DAYS",
+      "THIS_MONTH",
+      "LAST_MONTH"
+    ],
+    "type": "string"
+  },
+  {
+    "pattern": "\\ABETWEEN '([0-9]{4}-[0-9]{2}-[0-9]{2})' AND '([0-9]{4}-[0-9]{2}-[0-9]{2})'\\Z",
+    "type": "string"
+  },
+  {
+    "pattern": "\\A([0-9]{4}-[0-9]{2}-[0-9]{2})\\.\\.([0-9]{4}-[0-9]{2}-[0-9]{2})\\Z",
+    "type": "string"
+  }
+]
    • changedInput schema / properties / period / description
      Previous value: -"Reporting window for the metrics. Default 'LAST_30_DAYS'. Use a shorter window (LAST_7_DAYS / LAST_14_DAYS) when diagnosing recent changes; use LAST_90_DAYS for trend baselines. Also accepts an explicit range in GAQL spelling — \"BETWEEN 'YYYY-MM-DD' AND 'YYYY-MM-DD'\", both endpoints inclusive, in the account's time zone — for a window no trailing constant can reach (e.g. a single past calendar month). One asymmetry to know about: every constant except LAST_90_DAYS is resolved by Google Ads in the account's reporting time zone, whereas LAST_90_DAYS has no API constant and is expanded by mureo into the 90 days ending yesterday **on the server's date**, so its edges can differ by a day when the server and the account are in different zones. Pass an explicit range when the exact boundary matters."New value: +"Reporting window for the metrics. Default 'LAST_30_DAYS'. Use a shorter window (LAST_7_DAYS / LAST_14_DAYS) when diagnosing recent changes; use LAST_90_DAYS for trend baselines. Also accepts an explicit range — \"YYYY-MM-DD..YYYY-MM-DD\" (the spelling Meta Ads takes too) or, in GAQL spelling, \"BETWEEN 'YYYY-MM-DD' AND 'YYYY-MM-DD'\" — both endpoints inclusive, in the account's time zone, for a window no trailing constant can reach (e.g. a single past calendar month). One asymmetry to know about: every constant except LAST_90_DAYS is resolved by Google Ads in the account's reporting time zone, whereas LAST_90_DAYS has no API constant and is expanded by mureo into the 90 days ending yesterday **on the server's date**, so its edges can differ by a day when the server and the account are in different zones. Pass an explicit range when the exact boundary matters."
  2. Changed3 schema fields changedv0.17.1
    • addedInput schema / properties / period / anyOf
      Added value: +[
+  {
+    "enum": [
+      "TODAY",
+      "YESTERDAY",
+      "THIS_WEEK_SUN_TODAY",
+      "THIS_WEEK_MON_TODAY",
+      "LAST_BUSINESS_WEEK",
+      "LAST_WEEK_SUN_SAT",
+      "LAST_WEEK_MON_SUN",
+      "LAST_7_DAYS",
+      "LAST_14_DAYS",
+      "LAST_30_DAYS",
+      "LAST_90_DAYS",
+      "THIS_MONTH",
+      "LAST_MONTH"
+    ],
+    "type": "string"
+  },
+  {
+    "pattern": "\\ABETWEEN '([0-9]{4}-[0-9]{2}-[0-9]{2})' AND '([0-9]{4}-[0-9]{2}-[0-9]{2})'\\Z",
+    "type": "string"
+  }
+]
    • changedInput schema / properties / period / description
      Previous value: -"Reporting window for the metrics. Default 'LAST_30_DAYS'. Use a shorter window (LAST_7_DAYS / LAST_14_DAYS) when diagnosing recent changes; use LAST_90_DAYS for trend baselines."New value: +"Reporting window for the metrics. Default 'LAST_30_DAYS'. Use a shorter window (LAST_7_DAYS / LAST_14_DAYS) when diagnosing recent changes; use LAST_90_DAYS for trend baselines. Also accepts an explicit range in GAQL spelling — \"BETWEEN 'YYYY-MM-DD' AND 'YYYY-MM-DD'\", both endpoints inclusive, in the account's time zone — for a window no trailing constant can reach (e.g. a single past calendar month). One asymmetry to know about: every constant except LAST_90_DAYS is resolved by Google Ads in the account's reporting time zone, whereas LAST_90_DAYS has no API constant and is expanded by mureo into the 90 days ending yesterday **on the server's date**, so its edges can differ by a day when the server and the account are in different zones. Pass an explicit range when the exact boundary matters."
    • removedInput schema / properties / period / enum
      Removed value: -[
-  "TODAY",
-  "YESTERDAY",
-  "LAST_7_DAYS",
-  "LAST_14_DAYS",
-  "LAST_30_DAYS",
-  "LAST_90_DAYS",
-  "THIS_MONTH",
-  "LAST_MONTH"
-]
  3. Changed1 schema field changedv0.10.37
    • addedInput schema / additionalProperties
      Added value: +false
  4. Addedv0.10.11
  5. Removedv0.10.9
  6. Addedv0.9.12
  7. Removedv0.9.6
  8. Addedv0.9.2
  9. Removedv0.9.1
  10. Addedv1.0.5

TDQS

A4.6/5.0
Behavior5/5

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

No annotations exist, so the description carries the full burden and does: it declares 'Read-only', documents the exact return shape and sort order, states cpa is None when conversions == 0, and discloses the insight-firing heuristics and the no-data fallback ('message' field plus empty devices list). That is behavior an agent cannot infer from the schema.

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?

One dense, front-loaded paragraph that leads with what is compared and what is returned before edge cases and routing. Every clause earns its place, though the insight-rule and trailing disambiguation clauses make it heavier than strictly necessary for a read tool.

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?

There is no output schema, and the description fully compensates by specifying the response fields, sorting, null semantics, and empty-result behavior. Combined with the read-only declaration and sibling routing, an agent has everything needed to call and interpret it.

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 period parameter's schema text is unusually rich (constants, explicit ranges, time-zone asymmetry, LAST_90_DAYS caveat), so the schema already does the heavy lifting. The description itself mentions no parameter semantics, so baseline 3 applies rather than a higher score.

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?

The description opens with a specific verb+resource+scope: comparing Google Ads campaign performance across device segments (Desktop/Mobile/Tablet). It goes further than the name requires by disambiguating from the similarly named schedule-targeting sibling (hour-of-day config, NOT performance segmentation by hour), so an agent can tell them apart without opening either schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

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

Explicit routing: for applying device bid modifiers use google_ads_bid_adjustments_update or google_ads_device_targeting_set; for raw ad-schedule criteria use google_ads_schedule_targeting_list. That separates analysis from mutation and from a near-name-collision read tool, which is exactly the confusion this tool invites.

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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