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Google Trends MCP Server

compare_periods

Read-onlyIdempotent

Compare a keyword's Google Trends interest across two time ranges on one aligned scale, such as this year versus last year or this quarter versus the prior one.

Instructions

One term in two time ranges on the same scale: this year against last year, this quarter against the one before.

period: the range to look at (3m, 12m, 2026, 2026-03, or explicit dates; not hours). against: "year_before" (same dates a year earlier), "previous" (the range just before), or another range. The two curves are aligned by position, so day 10 of one sits beside day 10 of the other.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
geoNo
periodNo12m
pointsNo
againstNoyear_before
keywordYes
categoryNo
propertyNoweb

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already cover read-only, idempotent, open-world behavior, so the bar is lower. The description adds real behavioral context the annotations cannot: the two curves are aligned by position, so day 10 of one sits next to day 10 of the other. That alignment rule meaningfully affects how results should be read.

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 definition is front-loaded with the core concept and then uses labeled lines for the parameters that need explanation. It is compact and every sentence contributes; only the slightly terse opening framing ('one term') costs it a point.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return values need no explanation. However, for a 7-parameter tool with zero schema descriptions, the description omits too many parameters (points, geo, property, category) to be considered fully complete, even though the central comparison semantics are well covered.

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 coverage is 0% across 7 parameters, so the description carries the full burden. It documents the two most distinctive parameters well, spelling out accepted period formats and the three 'against' values, but leaves points, geo, property, and category entirely unexplained — notably 'points', which controls resolution and is not self-evident from its name.

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 states a specific capability: plotting one term across two time ranges on a shared scale, with concrete examples ('this year against last year'). It is clearly differentiable from nearby siblings like interest_over_time and compare_locations, though it never names them explicitly.

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 opening examples imply when the tool fits, and the 'against' options hint at comparison modes, but there is no explicit statement of when to prefer compare_periods over compare_locations, compare_many, or interest_over_time. Usage is implied rather than prescribed.

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