Google Search MCP Server

search_trends

Track search interest trends over time, discover emerging topics, and get predictive insights for up to five topics with regional and category filters.

Instructions

Track and analyze search interest trends over time with predictive insights and emerging topic discovery

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": {
      "topics": "<topics>"
    },
    "name": "search_trends"
  }
}

Input Schema

Name	Required	Description	Default
`topics`	Yes	Array of topics to track trends for (1-5 topics)
`timeframe`	No	Time period to analyze (1M=1 month, 3M=3 months, etc.)	6M
`region`	No	Geographic region for trend analysis (country code like US, GB, CA)	US
`category`	No	Category filter for more targeted trend analysis	all
`includePredictions`	No	Include trend prediction and forecasting
`relatedTopics`	No	Discover and include related trending topics

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0May 30, 2026

TDQS

C2.9/5.0

Behavior2/5

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

With no annotations provided, the description carries the full burden of disclosing behavioral traits. It only mentions tracking and analysis, but fails to specify whether the tool is read-only, how it handles predictions, or any side effects or limitations.

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 description is a single sentence that front-loads the core purpose. It is efficient, but could be slightly more structured to include differentiating details without adding length.

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?

Given the complexity of trend analysis and the lack of an output schema, the description is too brief. It does not explain what the tool returns, how to interpret predictions, or how the 'relatedTopics' and 'includePredictions' parameters affect results.

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 baseline is 3. The description does not add any parameter-specific meaning beyond what the schema already provides, but the schema itself is detailed enough.

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 clearly states the tool's purpose: tracking and analyzing search interest trends with predictive insights. However, it does not differentiate from the sibling 'search_analytics' tool, leaving ambiguity about when each should be used.

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 guidance is provided on when to use this tool versus alternatives like 'search_analytics' or other sibling tools. The description lacks any context about appropriate use cases or prerequisites.

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

Deploy Server