definitionsFetch dictionary definitions for a word from Wordnik; filter by part of speech, source dictionary, and limit. Returns definitions with source, text, and part of speech.
| Name | Required | Description | Default |
|---|---|---|---|
| word | Yes | ||
| limit | No | ||
| includeTags | No | ||
| partOfSpeech | No | ||
| useCanonical | No | ||
| includeRelated | No | ||
| sourceDictionaries | No |
| Name | Required | Description | Default |
|---|---|---|---|
| count | Yes | Number of items returned. | |
| items | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "word": "serendipity"
+ },
+ {
+ "limit": 5,
+ "partOfSpeech": "adjective",
+ "word": "ephemeral"
+ }
+]Output schema / (root)Previous value: -nullNew value: +{
+ "properties": {
+ "count": {
+ "description": "Number of items returned.",
+ "type": "integer"
+ },
+ "items": {
+ "items": {
+ "properties": {
+ "attributionUrl": {
+ "description": "Attribution URL",
+ "type": "string"
+ },
+ "definition": {
+ "description": "Definition text",
+ "type": "string"
+ },
+ "exampleUses": {
+ "description": "Usage examples",
+ "items": {
+ "properties": {
+ "text": {
+ "description": "Example usage text",
+ "type": "string"
+ }
+ },
+ "type": "object"
+ },
+ "type": "array"
+ },
+ "partOfSpeech": {
+ "description": "Part of speech",
+ "type": "string"
+ },
+ "relatedWords": {
+ "description": "Related words",
+ "items": {
+ "properties": {
+ "relationship": {
+ "description": "Relationship type",
+ "type": "string"
+ },
+ "word": {
+ "description": "Related word",
+ "type": "string"
+ }
+ },
+ "type": "object"
+ },
+ "type": "array"
+ },
+ "source": {
+ "description": "Dictionary source",
+ "type": "string"
+ },
+ "sourceDictionary": {
+ "description": "Source dictionary name",
+ "type": "string"
+ },
+ "tags": {
+ "description": "Tags",
+ "items": {
+ "type": "string"
+ },
+ "type": "array"
+ },
+ "word": {
+ "description": "The word being defined",
+ "type": "string"
+ }
+ },
+ "type": "object"
+ },
+ "type": "array"
+ }
+ },
+ "required": [
+ "items",
+ "count"
+ ],
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds context beyond annotations by specifying the source (Wordnik) and the return structure ('definitions with source, text, and part of speech'). Annotations already indicate read-only and non-destructive behavior, so no contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences. The first sentence delivers the core action and filters, and the second clarifies the return format. Every part is necessary and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema, the description does not need to detail return values. It covers the essential purpose and key filters. However, with 7 parameters and only 3 mentioned, some completeness is lost, but the tool's overall usage is still clear.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description only covers 3 out of 7 parameters (partOfSpeech, sourceDictionaries, limit), leaving includeTags, useCanonical, includeRelated, and the context of the 'word' parameter unaddressed. With 0% schema description coverage, the description should provide more parameter meaning but falls short.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Fetch dictionary definitions for a word'), the data source ('from Wordnik'), and the resource ('definitions'). It also distinguishes this tool from sibling tools like 'related', 'phrases', and 'pronunciations' which handle other word data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions filtering capabilities ('by part of speech, source dictionary, and limit') which implies when to use this tool for specific needs. However, it does not explicitly state when not to use it or compare it to alternatives like 'top_example' or 'related'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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 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.
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.
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.