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Unique Domains MCP server

Unique Domains MCP server

Official
by UniqueDomains
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

A word's Wikipedia and Wikidata facts

ud_get_word_notability
Read-onlyIdempotent

Retrieve Wikipedia and Wikidata notability facts for a word to judge how widely known it is as a public topic.

Instructions

A word's Wikipedia and Wikidata facts. Use it when someone asks how widely known a word is as a public topic. Pass word (such as harbor).

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": {
      "word": "<word>"
    },
    "name": "ud_get_word_notability"
  }
}

Input Schema

NameRequiredDescriptionDefault
wordYesThe catalog slug, the word, or `wrd_<id>`.
fieldsNoComma-separated top-level keys to keep: wikipediaTitle, backlinks, languages, wikidataId, description.

Output Schema

NameRequiredDescriptionDefault
dataNo
metaNoThe day of the answer, and the page cursor of a list.
linksNoLinks of the answer.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.4

TDQS

A3.8/5.0
Behavior3/5

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

The annotations already declare readOnly, idempotent, non-destructive, and closed-world, so the safety profile is covered. The description adds the notability framing but says nothing about data freshness, where the Wikipedia/Wikidata facts come from, or how sparse results can be for obscure words — useful context for a lookup tool. That is a modest, not rich, contribution beyond the structured fields.

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?

Two short sentences, front-loaded with the resource, followed by the trigger condition and a concrete example value. Nothing is padded or redundant.

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?

With an output schema present, the return shape needs no explanation, and annotations cover safety. Purpose, trigger, and a sample argument are all present; only the `fields` projection behavior and expectations about sparse results for unknown words are left unaddressed.

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%, including the accepted forms (catalog slug, plain word, `wrd_<id>`) and the full list of field keys. The description only restates the `word` parameter with an example ("harbor") and ignores `fields` entirely, so it adds marginal value over the schema.

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 names a specific resource — a word's Wikipedia and Wikidata facts — plus the underlying concept (notability / how widely known a word is as a public topic). That is enough to separate it from siblings like ud_get_word_market or ud_get_word_endings, though it never names an alternative explicitly.

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?

"Use it when someone asks how widely known a word is as a public topic" gives a concrete trigger condition tied to the user's question. It stops short of stating when NOT to use it or which sibling to prefer for adjacent questions (e.g. market data on a word).

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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