Skip to main content
Glama
rgellis

Google Search Console MCP Server

by rgellis

Top Queries

top_queries

Retrieve the search queries ranked by clicks for a given website property to analyze search performance.

Instructions

Top search queries by clicks for a property.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filtersNoSimplified filters combined with AND.
end_dateNoInclusive end date.
site_urlYesProperty identifier.
row_limitNoNumber of queries to return.
start_dateNoInclusive start date. Defaults to a 28-day window ending three days ago, so the last day is not partial.
search_typeNoReport type.WEB

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden, and it only discloses the click-based ordering. It says nothing about authentication requirements, rate limits, pagination, or whether results are truncated at row_limit, all of which matter for an analytics retrieval tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The single sentence is front-loaded and free of filler, but it is arguably under-sized rather than concise for a six-parameter analytics tool. Nothing is wasted, yet too little is said.

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

Completeness3/5

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

An output schema exists, so return values need not be explained, and the schema thoroughly documents parameters. However, with zero annotations and no usage or behavioral context, the definition leaves an agent without enough to confidently choose this tool over its many analytics siblings.

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 every parameter including the filters object and the default 28-day date window is already documented in the schema. The description adds no parameter-level meaning beyond the click-ordering hint, making 3 the correct baseline.

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 resource (search queries) and a ranking metric (by clicks) scoped to a property, which is enough to distinguish it from siblings like top_pages or performance_by_date. It stops short of explicitly naming those alternatives, so it doesn't reach the top tier.

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?

There is no guidance on when to use this tool versus query_search_analytics, query_all_rows, or top_pages, and no mention of prerequisites. The agent must infer usage purely from the name and resource.

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