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rgellis

Google Search Console MCP Server

by rgellis

Performance By Date

performance_by_date

Retrieve daily search performance metrics for a site property over a specified date range.

Instructions

Daily performance time series for a property.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filtersNoSimplified filters combined with AND.
end_dateNoInclusive end date.
site_urlYesProperty identifier.
row_limitNoMaximum days to return.
start_dateNoInclusive start date. Defaults to a 28-day window ending three days ago.
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 burden, yet it only restates the shape of the result. It says nothing about read-only behavior, authentication/scope requirements, rate limits, data freshness, or the default 28-day window semantics that drive results.

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?

A single eight-word sentence with no filler and a front-loaded subject. It is efficiently sized, though arguably too terse to carry any detail an agent could use.

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 covers all six parameters. However, given the dense sibling set of similar performance_* tools and the absence of annotations, the description omits any disambiguation or behavioral context needed to pick this tool confidently.

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 coverage is 100%, so every parameter (including filter combination semantics, inclusive date bounds, row_limit, and the search_type enum) is already documented in the schema. The description adds no syntax, format, or interaction detail beyond that, so the baseline of 3 applies.

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?

States a specific resource (performance) and a specific dimension (daily/date-based time series), which implicitly distinguishes it from the sibling dims performance_by_country and performance_by_device. It does not explicitly name an alternative, so it falls short of a 5.

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 when-to-use guidance, no mention of when to prefer it over performance_by_country/performance_by_device or query_search_analytics, and no prerequisites. The reader must infer intended usage from the name alone.

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