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mamrrez

Google Search Console MCP Server

query_variants

Read-onlyIdempotent

Group Search Console queries that differ by spelling or script, then combine their totals so split keywords report accurate combined performance.

Instructions

Keywords that Search Console splits across several spellings, with their real combined totals.

Groups queries by a per-script match key: Persian/Arabic letter forms (ی/ي, ک/ك, ه/ة, ا/أ/إ/آ), half-space, vowel marks, digit scripts, kana width, case, separator punctuation — also inside mixed queries such as «خريد iphone 13». level=loose additionally merges spacing, accents (café/cafe), hiragana/katakana, Simplified/Traditional Chinese (with the zh extra). Only groups with at least min_variants spellings are shown. source=history uses the local store.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNo
levelNostandard
limitNo
sourceNoapi
end_dateNo
max_rowsNo
site_urlYes
start_dateNo
search_typeNoweb
min_variantsNo
query_filterNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A3.5/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive and open-world, so the safety profile is covered. The description adds genuine extra context: groups below min_variants are hidden, level=loose widens merging (spacing, accents, kana, Chinese variants), and source=history reads the local store rather than the API.

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

Conciseness5/5

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

Purpose is front-loaded in the first sentence, and the following sentences each earn their place by defining the grouping rule and the level/source behaviors. Dense but no filler or repetition.

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 described, and the read-only nature is annotated. However, with 11 parameters at 0% schema coverage and no usage/routing guidance, an agent still lacks enough information to pick sensible values for the undocumented parameters.

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 0% across 11 parameters, so the description must compensate and it only partially does: it explains level, min_variants and source semantics, but days, limit, max_rows, search_type, query_filter, start_date/end_date and site_url are left entirely to inference.

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?

Starts with a specific verb-and-resource framing ('Keywords that Search Console splits across several spellings, with their real combined totals') and details the grouping key, which distinguishes it from siblings like keyboard_mistypes and top_terms. It never names a sibling explicitly, so it stops 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 / when-not-to-use guidance or named alternative. The description discusses level=loose and source=history as behavioral modes, which implies context, but an agent is not told when this tool should be chosen over top_terms or keyboard_mistypes.

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