Skip to main content
Glama

Serpapi

by io.github.pipeworx-io

Serpapi Google Trends

serpapi_google_trends
Read-onlyIdempotent

Get Google Trends interest-over-time for <terms> — returns the requested trends block (interest over time, by region, or related queries) via SerpApi. Example: serpapi_google_trends({ q: "bitcoin,ethereum", date: "today 12-m", geo: "US", _apiKey: "your-serpapi-key" })

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qYesUp to 5 comma-separated terms to compare, e.g. "bitcoin,ethereum"
geoNoOptional two-letter geo code to scope the trend, e.g. "US", "GB"
dateNoOptional time range, e.g. "today 12-m", "today 5-y", "2021-01-01 2021-12-31"
_apiKeyYesSerpApi API key (get one at serpapi.com)
data_typeNoTrends block to return (default "TIMESERIES"). One of TIMESERIES, GEO_MAP, GEO_MAP_0, RELATED_QUERIES

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare the tool as read-only, idempotent, and non-destructive. The description adds that it calls an external API (SerpApi) and requires an API key, which is useful context. However, it does not mention potential rate limits, error handling, or response delays.

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?

One concise sentence describing purpose and output, plus a clear example. No redundant or unnecessary information.

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

Completeness2/5

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

No output schema is present, and the description only vaguely states it returns 'the requested trends block'. For a tool with no output schema, the description should provide more detail on the return structure (e.g., fields, format). This gap reduces completeness.

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 each parameter is already documented. The description provides an example but does not add new semantic meaning beyond the schema. Baseline 3 is appropriate.

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 clearly states it retrieves Google Trends interest-over-time data for specified terms, and distinguishes itself from sibling tools (e.g., serpapi_google_news, serpapi_google_jobs) by specifying 'Google Trends' and describing the data blocks returned.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool over alternatives (e.g., other SerpApi tools). The example shows usage but does not provide decision criteria, scope, or prerequisites beyond having an API key.

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

All Serpapi toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.8/5.0
Disambiguation3/5

Many tools have overlapping purposes, such as ask_pipeworx, ask_pipeworx_grounded, deep_research, and bet_research all querying data but with nuanced differences. The descriptions help but boundaries remain fuzzy, especially between ask_pipeworx and deep_research for broad vs. single lookups. Overall moderate ambiguity.

Naming Consistency2/5

Naming is inconsistent: some tools use snake_case (ask_pipeworx, ai_visibility_check), others use camelCase (serpapi_google_jobs), and patterns vary widely (e.g., pipeworx_feedback vs. compare_entities). Only the serpapi_google_* group follows a consistent pattern.

Tool Count3/5

36 tools is on the high side for a single server, with many meta-tools (discover_tools, suggest_questions) and niche prediction market tools. The scope seems overly broad, covering data lookup, prediction markets, memory, and subscriptions, which could be streamlined to a more focused set.

Completeness3/5

The server covers a wide range of domains (financial, economic, news, drugs, prediction markets, Google services), but lacks direct web search and write/update capabilities. While the coverage is broad, there are notable gaps (e.g., no generic web search, limited tool for modifying data) for a data-focused server.

Resources