Google Search MCP Server

search_analytics

Analyze search trends from multiple queries by adjusting time range and result limits. Gain insights into search behavior patterns.

Instructions

Analyze search trends and get insights from multiple search queries

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": {
      "queries": "<queries>"
    },
    "name": "search_analytics"
  }
}

Input Schema

Name	Required	Description	Default
`queries`	Yes	Array of search queries to analyze
`timeRange`	No	Time range for trend analysis	month
`maxResults`	No	Maximum results per query

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0May 30, 2026

TDQS

C2.7/5.0

Behavior2/5

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

No annotations are provided, so the description must convey behavioral traits. It does not disclose rate limits, authentication needs, whether the operation is read-only, or what happens with invalid inputs. The description is too brief to compensate for the lack of annotations.

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, front-loaded sentence that efficiently conveys the core purpose. It is concise with no wasted words, though it could benefit from more detail.

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 tool's complexity (3 parameters, no output schema), the description is incomplete. It does not explain what kind of insights are returned, the format, or any limitations. For a tool that analyzes multiple queries, more context is needed for an AI agent to use it effectively.

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

Parameters2/5

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

The input schema has 100% description coverage, so the baseline is 3. However, the description adds no additional meaning beyond the schema; it simply restates the purpose without detailing parameters. It does not clarify the expected format or usage of queries, timeRange, or maxResults beyond what the schema already provides.

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 that the tool analyzes search trends and provides insights from multiple queries. It distinguishes itself from sibling tools like google_search (raw results) and search_trends (possibly a different focus), though not explicitly.

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 given on when to use this tool versus alternatives. With siblings like academic_search, fact_checker, and news_monitor, the description lacks context for choosing among them.

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

Deploy Server