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Yandex Wordstat MCP

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TypeScript
Remote

Топ и похожие запросы

top_requests
Read-onlyIdempotent

Retrieve search demand for a phrase over the last 30 days: queries containing it, semantically similar queries, and total counts, with optional region and device filters for keyword research.

Instructions

Возвращает поисковый спрос по фразе за последние 30 дней: самые популярные запросы, которые СОДЕРЖАТ фразу (results), и семантически ПОХОЖИЕ запросы, которые могут её не содержать (associations), плюс totalCount. Подходит для подбора ключевых фраз и оценки спроса. Значения счётчиков могут приходить строками (int64). Необязательные regionIds и devices сужают выборку; numPhrases задаёт, сколько фраз вернуть (1..2000).

Input Schema

NameRequiredDescriptionDefault
phraseYesПоисковая фраза для анализа, например «купить велосипед».
devicesNoФильтр по устройствам: любые из all, desktop, phone, tablet. Без параметра — все устройства.
regionIdsNoId регионов, которыми ограничить спрос, например [213] (Москва), [2] (Санкт-Петербург). Id берутся из list_regions. Без параметра — все регионы.
numPhrasesNoСколько топовых фраз вернуть (1..2000; по умолчанию 20).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changedv2.4.0
    • changedInput schema / properties / devices / description
      Previous value: -"Device filter: any of all, desktop, phone, tablet. Omit for all devices."New value: +"Фильтр по устройствам: любые из all, desktop, phone, tablet. Без параметра — все устройства."
    • changedInput schema / properties / numPhrases / description
      Previous value: -"How many top phrases to return (1..2000; default 20)."New value: +"Сколько топовых фраз вернуть (1..2000; по умолчанию 20)."
    • changedInput schema / properties / phrase / description
      Previous value: -"The search phrase to research, e.g. «купить велосипед»."New value: +"Поисковая фраза для анализа, например «купить велосипед»."
    • changedInput schema / properties / regionIds / description
      Previous value: -"Region ids to scope demand to, e.g. [213] (Moscow), [2] (St. Petersburg). Get ids from list_regions. Omit for all regions."New value: +"Id регионов, которыми ограничить спрос, например [213] (Москва), [2] (Санкт-Петербург). Id берутся из list_regions. Без параметра — все регионы."
  2. Changed1 schema field changedv2.0.1
    • changedInput schema / properties / regionIds / items / anyOf
      Previous value: -[
-  {
-    "type": "integer"
-  },
-  {
-    "type": "string"
-  }
-]New value: +[
+  {
+    "type": "integer"
+  },
+  {
+    "pattern": "^\\d+$",
+    "type": "string"
+  }
+]
  3. Changed1 schema field changedv2.0.0
    • changedInput schema / properties / numPhrases / description
      Previous value: -"How many top phrases to return (cloud flavor only; default 20). Ignored on the oauth flavor."New value: +"How many top phrases to return (1..2000; default 20)."
  4. First observedv0.1.0

TDQS

A4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint and openWorldHint, so the description doesn't need to re-establish safety. It does add real behavioral context: the two-bucket result structure and the caveat that counters may arrive as strings (int64), which is non-obvious and valuable. It does not cover rate limits, ordering, or pagination behavior, so it stays at a moderate score.

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?

Three sentences, front-loaded with the return structure and then the type caveat and parameter hints. Dense but every clause carries information; minor redundancy with the schema on parameter ranges keeps it from a 5.

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

Completeness5/5

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

There is no output schema, so the description carries the burden of explaining returns — and it does: names results, associations and totalCount and flags the int64-as-string quirk. Together with complete schema descriptions for all parameters, an agent has everything needed to call and interpret this tool.

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 all four parameters are already documented in the schema with examples and defaults. The description only restates that regionIds/devices narrow the sample and numPhrases is 1..2000 — no syntax or semantics beyond the schema. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource (returns search demand for a phrase over the last 30 days) and explicitly distinguishes the two result buckets: results (containing the phrase) and associations (semantically similar, may not contain it), plus totalCount. This is far more precise than the tool name and lets an agent understand the payload without opening a schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives a clear usage context (keyword selection and demand estimation) and tells the agent that regionIds and devices narrow the sample. However, it never names an alternative sibling — e.g. when to prefer dynamics or regions — so the agent gets context but no explicit routing against alternatives.

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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