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bypixels

SEO MCP PRO

by bypixels

gsc_query_performance

Pull Google Search Console search performance metrics for queries, pages, countries, devices, and dates. Use this data to identify SEO opportunities and track ranking changes.

Instructions

Queries search performance data from Google Search Console

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNo
endDateYesEnd date in YYYY-MM-DD format
siteUrlYesSite URL (e.g., https://example.com/ or sc-domain:example.com)
rowLimitNo
startRowNo
dataStateNo
startDateYesStart date in YYYY-MM-DD format
dimensionsNo
aggregationTypeNo
dimensionFilterGroupsNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

C2.6/5.0
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 behavioral disclosure, but it only states that the tool queries data. It does not mention pagination (startRow/rowLimit), dataState behavior, filtering semantics, or required GSC verification/permissions.

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 clear sentence with no filler and gets the main point across quickly. It is concise, though it sacrifices helpful 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?

For a tool with 10 parameters, no output schema, and no annotations, a one-sentence description is insufficient. It omits return-value shape, default behavior, and the meaning of core options, leaving an agent to infer too much.

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

Parameters1/5

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

Schema description coverage is only 30% and the description adds no parameter details. Seven parameters (type, rowLimit, startRow, dataState, dimensions, aggregationType, dimensionFilterGroups) are undocumented in both the schema and description, so the agent has no semantic guidance for them.

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 identifies the action (queries) and the resource (search performance data from Google Search Console), and the tool name reinforces this. However, it does not differentiate itself from sibling tools like gsc_top_queries or gsc_top_pages, which also query GSC performance data.

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 about when to choose this tool over alternatives or in which scenario it applies. An agent cannot tell this from gsc_top_queries or gsc_coverage_report based on the description alone.

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

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