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dex-data

dex-data

by donnywin85
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Remote

get_search_suggestions

Get search suggestions and related queries for a topic, expanded across question and comparison modifiers, to identify demand signals for keyword and content research.

Instructions

What people actually type into a search box for a topic — live search autocomplete, expanded across question modifiers (how/what/why/is/can/does) and comparison modifiers (vs/or), then split into suggestions, questions and comparisons. Rows where the engine dropped your term and answered something else are filtered out and counted. A demand signal for content and keyword research, not a ranking — search volume is not published upstream and is not invented.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "q": "<q>"
    },
    "name": "get_search_suggestions"
  }
}

Input Schema

NameRequiredDescriptionDefault
qYesTopic or search terms, max 200 characters.
langNoLanguage code, default "en".
depthNo"full" (default) expands across 15 modifiers; "basic" returns completions for the query alone.
countryNoTwo-letter market code, default "us".

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations, the description carries the transparency burden. It discloses that it is not a ranking and that it filters out dropped terms, and it explains the output format (suggestions, questions, comparisons). It does not mention rate limits or API-side behaviors, but the data-processing transparency is good.

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 two sentences and relatively concise, though it uses dense phrasing like 'live search autocomplete, expanded across question modifiers'. It stays focused on the tool's function and output without unnecessary detail.

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?

Although there is no output schema, the description explains the return structure ('split into suggestions, questions and comparisons') and the filtering behavior, which is sufficient for an agent to understand what the tool will produce. It lacks explicit examples or edge-case handling, but covers essential context.

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?

The schema provides 100% coverage of parameter descriptions, so the description adds no extra value for parameters. It merely restates the schema's semantics (e.g., 'expanded across question modifiers' relates to depth, but this is not explicitly linked). The baseline for high schema coverage is 3, and the description does not elevate it.

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 clearly states the tool's purpose: to retrieve search autocomplete suggestions for a topic, expanded across question and comparison modifiers. It explicitly differentiates it from ranking tools, calling it 'a demand signal for content and keyword research, not a ranking', which distinguishes it from siblings like 'search'.

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 implies when to use the tool (for demand research) and notes that rows where the engine dropped the term are filtered out, giving insight into data handling. However, it does not explicitly mention alternative tools or provide a direct 'use this when' statement, though the context makes this clear.

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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