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semrush-ai-mcp

Related Keywords

semrush_related_keywords

Discover related keywords, synonyms, and variations with search volume and CPC for content ideation and keyword clustering.

Instructions

Full-search related keywords: variations, synonyms and semantically related phrases with volume and CPC. Ideal for content ideation and keyword clustering.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of rows to return (default 10). More rows = more API units.
phraseYes
databaseNoRegional database code, e.g. us, uk, de, fr, es, it, br, au, ca, in (default: us)us

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.2/5.0
Behavior2/5

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

With no annotations and no output schema, the description carries the full burden but only states what data is returned. It says nothing about API unit consumption, authentication, rate limits, or whether the seed phrase is required, all of which matter for a paid Semrush endpoint.

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?

Two tight sentences with the resource and output front-loaded and the use case following; there is no filler, though 'full-search' is slightly jargon-y without explanation.

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?

For a 3-parameter tool with no annotations or output schema, the description covers the returned metrics but omits the meaning of the required seed parameter, regional database behavior, and unit costs. It is adequate but has visible gaps.

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 67% (limit and database are documented with defaults and unit-cost notes), so the schema does most of the work. The description adds no meaning to the undocumented 'phrase' parameter beyond implying it is the seed term, leaving its role 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?

The description states a specific verb and resource ('full-search related keywords') and enumerates the returned data types (variations, synonyms, semantically related phrases with volume and CPC). An agent can distinguish this from sibling 'keyword_overview' or 'keyword_questions' by the type of terms returned, though no sibling is named explicitly.

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

Usage Guidelines3/5

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

It offers a use-case hint ('ideal for content ideation and keyword clustering') but gives no explicit when-to-use vs when-not guidance and does not point to alternative tools like semrush_keyword_overview or semrush_keyword_questions. Usage is only implied.

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