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AKzar1el

TrendPulse - Google News & Trends

by AKzar1el
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_interest_by_region

Read-only

Compare Google Trends search interest across countries, regions, cities, or DMAs for given keywords. Identify where demand is strongest to target campaigns effectively.

Instructions

Return geographic Google Trends interest for one or more known keywords at country, region, city, or DMA resolution. Use this to compare where demand is strongest; use get_trends for interest over time instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
catNoCategory ID (default: 0 for all).
geoNoGeographic region code (e.g. 'US' or empty '' for worldwide).US
gpropNoGoogle property filter.
keywordsYesSearch keyword(s) to analyze.
timeframeNoTimeframe for search volume analysis (e.g., 'today 12-m').today 12-m
resolutionNoGeographic resolution.REGION
inc_low_volNoInclude regions with low search volume.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed5 schema fields changedv0.2.22
    • changedInput schema / properties / gprop / description
      Previous value: -"Google property filter (e.g., '', 'youtube', 'news', 'images', 'froogle')."New value: +"Google property filter."
    • addedInput schema / properties / gprop / enum
      Added value: +[
+  "",
+  "youtube",
+  "news",
+  "images",
+  "froogle"
+]
    • changedInput schema / properties / keywords / anyOf
      Previous value: -[
-  {
-    "type": "string"
-  },
-  {
-    "items": {
-      "type": "string"
-    },
-    "type": "array"
-  }
-]New value: +[
+  {
+    "minLength": 1,
+    "type": "string"
+  },
+  {
+    "items": {
+      "minLength": 1,
+      "type": "string"
+    },
+    "maxItems": 5,
+    "minItems": 1,
+    "type": "array"
+  }
+]
    • changedInput schema / properties / resolution / description
      Previous value: -"Geographic resolution: 'COUNTRY', 'REGION', 'CITY', or 'DMA'."New value: +"Geographic resolution."
    • addedInput schema / properties / resolution / enum
      Added value: +[
+  "COUNTRY",
+  "REGION",
+  "CITY",
+  "DMA"
+]
  2. Changed1 schema field changedv0.2.13
    • removedOutput schema / description
      Removed value: -"Generic wrapper for non-object return types."
  3. First observed

TDQS

A4.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, openWorldHint=true, and destructiveHint=false, covering the safety profile. The description adds the geographic resolution scope and the 'known keywords' nuance, which is useful but not extensive. It doesn't describe return format or pagination, but that's covered by the output schema and annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with zero wasted words. The core purpose is front-loaded, and the alternative tool is named in the second sentence. This is an exemplary concise structure.

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?

The tool has 7 parameters but the schema fully describes each, and an output schema exists so return values don't need to be explained. The description covers the primary usage distinction (geographic vs. time-based) and the resolution options. It is complete for an agent to call correctly; the only minor gap is not stating that keywords must be exact known terms, but that is implied by 'known keywords' and the schema's string type.

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 all parameters already have clear descriptions. The description mentions 'known keywords' and resolution levels, but these are already implied in the schema. With full schema coverage, the baseline of 3 is appropriate; the description adds minimal extra meaning beyond what the schema provides.

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 states a specific verb ('Return'), a resource ('Google Trends interest'), and the scope ('geographic ... at country, region, city, or DMA resolution'). It explicitly differentiates from the sibling get_trends by noting that get_trends handles interest over time, so an agent can immediately tell this tool apart.

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?

The description gives explicit guidance: 'Use this to compare where demand is strongest; use get_trends for interest over time instead.' This tells the agent when to use this tool and when to use an alternative, leaving nothing to inference.

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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