Wordnik

Random Words

random_words

Read-onlyIdempotent

Return up to limit random words from Wordnik; filter by part of speech, min/max length, and minimum corpus or dictionary occurrence count.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`limit`	No
`maxLength`	No
`minLength`	No
`minCorpusCount`	No
`hasDictionaryDef`	No
`minDictionaryCount`	No
`excludePartOfSpeech`	No
`includePartOfSpeech`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
`count`	Yes	Number of items returned.
`items`	Yes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

Changed2 schema fields changedMay 27, 2026

addedInput schema / examples

Added value: +[
+  {
+    "hasDictionaryDef": true,
+    "limit": 10,
+    "minDictionaryCount": 1
+  }
+]

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "properties": {
+    "count": {
+      "description": "Number of items returned.",
+      "type": "integer"
+    },
+    "items": {
+      "items": {
+        "properties": {
+          "id": {
+            "description": "Word ID",
+            "type": "number"
+          },
+          "word": {
+            "description": "Random word",
+            "type": "string"
+          }
+        },
+        "type": "object"
+      },
+      "type": "array"
+    }
+  },
+  "required": [
+    "items",
+    "count"
+  ],
+  "type": "object"
+}

First observedMay 20, 2026

TDQS

A4/5.0

Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, covering safety. The description adds context about filtering but does not disclose whether results are truly random or deterministic (potentially conflicting with idempotentHint).

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?

The description is a single, well-structured sentence that front-loads the main action and immediately conveys the tool's purpose and key parameters without extraneous details.

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?

Given the tool's 8 parameters, no required fields, and an output schema, the description covers the main filtering dimensions. It does not mention pagination or defaults, but the output schema likely explains the return format, making the description fairly complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description adds meaning by naming filter categories (part of speech, min/max length, corpus/dictionary counts). It does not explicitly mention 'hasDictionaryDef', but the overview is helpful for an agent.

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 verb 'Return' and the resource 'random words from Wordnik', distinguishing it from siblings like 'random_word' (likely singular) by specifying multiple words and filters.

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?

The description implies use when needing random words with specific constraints, but it lacks explicit guidance on when to avoid this tool or compare to alternatives like 'definitions' or 'random_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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TDQS

B3.1/5.0

Disambiguation4/5

Most tools have clearly distinct purposes, especially between Wordnik and Pipeworx domains. However, some overlap exists among data query tools (e.g., ask_pipeworx vs deep_research) and company lookups (entity_profile vs compare_entities), but descriptions are detailed enough to differentiate them in most cases.

Naming Consistency3/5

Naming conventions are mixed: some tools use snake_case (ai_visibility_check), others use descriptive phrases (ask_pipeworx_grounded), and some are single words (remember, recall). There is no uniform verb_noun pattern, though groups like polymarket_* and scan_* provide some consistency within their subsets.

Tool Count2/5

With 42 tools, the server is overloaded. It combines two distinct services (Wordnik dictionary and Pipeworx data) into one set, making it feel like two servers merged. Many tools are niche (e.g., hyphenation, random_words), increasing count without clear benefit. A split would improve coherence.

Completeness4/5

The Wordnik coverage is thorough (definitions, examples, pronunciation, frequency, etc.), and Pipeworx covers a wide range of data sources with tools for basic lookups, comparisons, research, and subscriptions. Minor gaps exist (e.g., no update/delete for Wordnik data), but overall the surface is comprehensive for the intended use.

Random Words

Input Schema

Output Schema

Schema Changelog

TDQS

Glama MCP Gateway

TDQS

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