google-trends

Google Trends interest over time

interest_over_time

Compare search interest for 1–5 keywords across a selected time range and location to identify whether their popularity is rising or falling.

Instructions

Compare search interest for 1-5 keywords over a time range (0-100 relative scale, like the Google Trends chart). Use this to see whether something is rising or falling in popularity.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "keywords": "<keywords>"
    },
    "name": "interest_over_time"
  }
}

Input Schema

Name	Required	Description	Default
`geo`	No	Country or region code, e.g. US, GB, IN, PK, US-CA	US
`keywords`	Yes	1 to 5 search terms to compare
`timeframe`	No	Google Trends time range	today 3-m

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Nov 11, 2026

TDQS

A3.6/5.0

Behavior3/5

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

With no annotations supplied, the description carries the full burden. It usefully discloses the relative 0-100 normalization ('like the Google Trends chart'), which is real behavioral context, but says nothing about rate limits, error behavior when a keyword has insufficient data, or how comparison across keywords is calculated.

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 tight sentences with the capability and the scale stated first, followed by the use case. No filler, no repetition of structured fields beyond what is needed to frame the output.

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?

For a three-parameter, read-only lookup with no output schema, the description covers the essentials: input shape (1-5 keywords, time range) and the meaning of the returned values (0-100 relative scale). The remaining gap is a lack of guidance on interpreting sparse or zero-volume results and on how this differs from sibling trend tools.

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 three parameters (geo, keywords, timeframe) are already documented with defaults, patterns, and an enum. The description only restates the 1-5 keyword limit and the notion of a time range, adding no syntax or constraint detail beyond the schema, so the baseline of 3 is appropriate.

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 names a specific verb and resource ('Compare search interest for 1-5 keywords over a time range') and specifies the output scale (0-100 relative). It is clear what the tool produces, though it never names the sibling tools (related_queries, trending_now) it is distinct from, so differentiation is left to inference.

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?

'Use this to see whether something is rising or falling in popularity' gives one intended use case, which implies when to reach for it. However, there is no when-not guidance and no routing to alternatives such as related_queries or trending_now for related but different questions.

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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