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keyword_trends

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Checks whether keywords are rising, stable, or declining over time using country-level Google Trends interest data across 3-month to 5-year periods.

Instructions

Use when checking if a keyword is rising, stable, or declining over time. Returns one series per keyword: interest data points (weekly or monthly — see granularity; each point has date), peak_month (null when the keyword has no data), trend_direction, and has_data. The in-progress week/month is left out (partial_period_excluded). IMPORTANT: interest data is country-level (volume_scope: "country") — Google Trends via this source has no city/state granularity; check location_used for the actual scope. Periods: 3m, 6m, 12m (default), 5y. Costs 9 credits.

Input Schema

Name	Required	Description
`period`	No	Time period. Default: "12m"
`keywords`	Yes	Keywords to get trends for
`location`	Yes	Geographic location (e.g. "Orchard Park, NY")

Output Schema

Name	Required	Description	Default
`period`	Yes
`trends`	Yes
`keywords`	Yes
`location`	Yes
`data_source`	No
`total_count`	Yes
`volume_scope`	No
`location_used`	No
`location_alternatives`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedv1.1.0Oct 22, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "$schema": "http://json-schema.org/draft-07/schema#",
+  "additionalProperties": true,
+  "properties": {
+    "data_source": {
+      "type": "string"
+    },
+    "keywords": {
+      "items": {
+        "type": "string"
+      },
+      "type": "array"
+    },
+    "location": {
+      "type": "string"
+    },
+    "location_alternatives": {
+      "items": {
+        "additionalProperties": true,
+        "properties": {
+          "code": {
+            "type": "number"
+          },
+          "name": {
+            "type": "string"
+          },
+          "type": {
+            "type": "string"
+          }
+        },
+        "required": [
+          "name",
+          "code",
+          "type"
+        ],
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "location_used": {
+      "type": "string"
+    },
+    "period": {
+      "type": "string"
+    },
+    "total_count": {
+      "type": "number"
+    },
+    "trends": {
+      "items": {
+        "additionalProperties": true,
+        "properties": {
+          "data_points": {
+            "items": {
+              "additionalProperties": true,
+              "properties": {
+                "date": {
+                  "type": "string"
+                },
+                "interest": {
+                  "type": "number"
+                },
+                "month": {
+                  "type": "string"
+                }
+              },
+              "required": [
+                "month",
+                "interest"
+              ],
+              "type": "object"
+            },
+            "type": "array"
+          },
+          "granularity": {
+            "enum": [
+              "daily",
+              "weekly",
+              "monthly",
+              "unknown"
+            ],
+            "type": "string"
+          },
+          "has_data": {
+            "type": "boolean"
+          },
+          "keyword": {
+            "type": "string"
+          },
+          "partial_period_excluded": {
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "peak_month": {
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "trend_direction": {
+            "enum": [
+              "rising",
+              "declining",
+              "stable"
+            ],
+            "type": "string"
+          }
+        },
+        "required": [
+          "keyword",
+          "data_points",
+          "peak_month",
+          "trend_direction"
+        ],
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "volume_scope": {
+      "enum": [
+        "local",
+        "country"
+      ],
+      "type": "string"
+    }
+  },
+  "required": [
+    "trends",
+    "total_count",
+    "keywords",
+    "location",
+    "period"
+  ],
+  "type": "object"
+}

First observedv0.1.0May 11, 2026

TDQS

A4.3/5.0

Behavior5/5

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

Beyond the annotations, the description discloses important behavior: the in-progress week/month is omitted, interest data is country-level with no city/state granularity, peak_month can be null, and the tool costs 9 credits. These are exactly the operational details an agent needs to invoke it correctly.

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?

The description is front-loaded with the usage condition and keeps important caveats near the end. It is dense but largely purposeful, though it enumerates return fields even though an output schema exists.

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?

Given the output schema and annotations, the description is complete: it covers when to use the tool, supported periods, cost, return shape, missing-data behavior, and the critical country-level limitation. An agent has enough context to select and invoke it correctly.

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%, so the baseline is 3, but the description adds useful meaning by clarifying the period options and default and warning that location resolves to country-level scope via location_used. It also indicates one series is returned per keyword.

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?

The description clearly states that the tool checks whether a keyword is rising, stable, or declining over time, and it summarizes the returned trend data. It does not explicitly differentiate this from sibling keyword tools such as search_volume, keyword_overview, or keyword_opportunities.

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?

It gives a clear usage context: use when checking keyword trend direction over time. It also notes the supported periods, default period, credit cost, and country-level limitation, but it does not name alternatives or state when not to use this tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.