Skip to main content
Glama

keyword_ideas

Generate related keyword and query ideas from a seed term using Google Suggest. Find free related search suggestions without search volume data.

Instructions

Get related keyword/query ideas for a seed term via Google Suggest (free; related queries only, no search volume).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
langNoLanguage code, e.g. "en" (default)
seedYesSeed keyword or phrase

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.1.9
    • addedInput schema / $schema
      Added value: +"http://json-schema.org/draft-07/schema#"
  2. First observedv0.1.0

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does meaningfully discharge part of it: it discloses the underlying source (Google Suggest), the cost profile (free), and a hard output limitation (no search volume, related queries only). It omits rate limits, authentication needs, and result-set size, which are the remaining behavioral gaps.

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?

One sentence, front-loaded with the action and resource, with the clarifying constraints tucked into a compact parenthetical. Every clause earns its place.

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

Completeness4/5

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

For a two-parameter, no-output-schema tool this covers purpose, source, cost, and the key output caveat. The main omission is any hint about the shape or volume of returned ideas and whether 'lang' materially changes results, but nothing critical to invoking it correctly is missing.

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% and both parameters are documented there, so the description needn't restate them. It references the seed concept implicitly but adds no format or syntax detail (e.g., how to handle multi-word phrases), so 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?

States a specific verb (Get) and resource (related keyword/query ideas) plus the data source (Google Suggest), which is exactly what an agent needs to know. It is unmistakably distinct from the sibling audit/robots/sitemap tools, so no sibling disambiguation is required.

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?

The parenthetical 'free; related queries only, no search volume' tells the agent when this is the right pick (a no-cost, related-term expansion) and implicitly when it is not (when search volume is needed). It stops short of naming an alternative tool for volume-bearing keyword data, so it is clear context rather than a full when/when-not routing rule.

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