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jain-eshan

Google Trends MCP

by jain-eshan
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

interest_over_time

Compare relative Google search interest for up to 5 keywords over time, returning 0-100 scores across chosen timeframe and geography to reveal trends.

Instructions

Relative Google search interest (0-100) over time for up to 5 keywords, compared side by side.

Args: keywords: 1-5 search terms to compare. Only the first 5 are used; additional keywords are silently dropped. timeframe: pytrends timeframe string, e.g. "today 12-m", "today 5-y", "now 7-d", or "YYYY-MM-DD YYYY-MM-DD". geo: ISO country code (e.g. "US", "IN", "GB"), or "" for worldwide (default). response_format: "concise" (default) covers the whole requested timeframe, thinned to about 26 evenly spaced points (first and last always kept) and rounded to whole numbers, so the shape of the window is intact at a low token cost. "full" returns every point unrounded - use it when you need week-by-week detail.

Returns: A list of records, one per date, each containing: - "date": ISO date string - "isPartial": present and true only when the period is incomplete (most recent point) - omitted when false in "concise" mode, since false is the common case. - One numeric key per keyword (0-100 relative interest value)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
geoNo
keywordsYes
timeframeNotoday 12-m
response_formatNoconcise

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv1.0.0
    • changedInput schema / properties / geo / default
      Previous value: -"IN"New value: +""
    • addedInput schema / properties / response_format
      Added value: +{
+  "default": "concise",
+  "title": "Response Format",
+  "type": "string"
+}
  2. First observedv0.1.0

TDQS

A4.8/5.0
Behavior5/5

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

With no annotations, the description carries full behavioral disclosure. It reveals key quirks: extra keywords beyond 5 are silently dropped, 'concise' mode thins to ~26 evenly spaced points with rounding, and 'isPartial' appears only for incomplete periods. This is unusually transparent and useful for an agent.

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?

The description is long but every section earns its place: purpose, parameter semantics, and return format. It is front-loaded with the core purpose and structured into Args/Returns, making it easy for an agent to scan.

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, so the return-structure explanation is essential and provided in detail: date, isPartial semantics, and per-keyword interest values. All four parameters are covered, and the behavioral nuances are disclosed. Nothing critical is missing for an agent to invoke the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description must document all parameters. It does so comprehensively: keywords with the 1-5 limit and drop behavior, timeframe with pytrends string examples, geo with country-code examples and default, and response_format with both modes fully explained.

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 and resource: it retrieves relative Google search interest (0-100) over time for up to 5 keywords. It also communicates the comparative, time-series nature that distinguishes it from siblings like interest_by_region or related_topics.

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?

The description clearly conveys the tool's context: search-interest trends over time, compared across keywords, with geographic filtering. It also gives specific guidance on when to use 'concise' vs 'full' response formats. It does not explicitly name alternatives or exclusion conditions, but the intended use is strongly implied.

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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