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Google Trends MCP Server

snapshot_trending

Idempotent

Save the current Trending Now list to local history so trends remain searchable after Google drops them.

Instructions

Save the current Trending Now list to the local history, so it can still be searched after Google drops it.

Google shows a trend for about a week; after that there is no way to ask what was trending. Each call stores every trend for the given countries (a trend seen again is updated, not duplicated). Run it on a schedule — gtrends-mcp-full snapshot US,GB from cron does the same — and use trending_history to query the result.

geos: comma-separated country or region codes (up to 12); blank = the default location, else US. hours: look-back window to save, 1-191. 24 is right for a daily schedule.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
geosNo
hoursNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.7/5.0
Behavior4/5

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

Annotations declare readOnlyHint=false, idempotentHint=true, destructiveHint=false and openWorldHint=true; the description reinforces this by stating that re-seen trends are updated rather than duplicated, which explains the idempotency in user terms. It also discloses the retention rationale and per-country scope. It does not say where history is stored or whether writes need any setup, so it stops short of full disclosure.

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?

Front-loaded with the action and rationale, then parameters, then the scheduling hint. The embedded CLI invocation and the 'run it on a schedule' aside add a little redundancy against the cron sentence, but every sentence still carries usable information.

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?

With an output schema present, return values need not be explained. The description covers purpose, motivation, scheduling guidance, parameter formats, dedupe behavior, and the sibling tool for retrieval, which is everything an agent needs to call it 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 description coverage is 0%, so the description carries the load and does so well: geos is described as comma-separated country/region codes, up to 12, with blank meaning the default location else US; hours is bounded 1-191 with 24 recommended for a daily run. Both parameters gain meaning absent from the bare schema.

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?

States a specific verb and resource ('Save the current Trending Now list to the local history') and immediately explains the motivating constraint (Google drops trends after about a week). It is clearly distinguishable from trending_now (live read) and trending_history (the query side, which it names).

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?

Explicitly tells the agent to run it on a schedule, gives a concrete example (cron with `gtrends-mcp-full snapshot US,GB`), recommends hours=24 for a daily cadence, and routes follow-up queries to trending_history. When-to-use and what-to-do-next are both spelled out.

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