PatSnap MCP Server

get_word_cloud

Generate a word cloud from recent patents to identify key terms and trends for refining patent searches and analysis.

Instructions

Obtain a snapshot of frequently occurring keywords/phrases from the most recent 5,000 published patents. Identify common terms for refining searches. Returns up to 100 keywords. Either keywords or IPC classification must be specified.

Input Schema

TableJSON Schema

Name	Required	Description
`keywords`	No	Keywords to search within patent title and abstract/summary. Supports AND, OR, NOT logic. Example: "mobile phone AND (screen OR battery)"
`ipc`	No	Patent IPC classification code. Used to specify a particular technology field.
`apply_start_time`	No	Patent application start year (yyyy format). Filters by application filing date.
`apply_end_time`	No	Patent application end year (yyyy format). Filters by application filing date.
`public_start_time`	No	Patent publication start year (yyyy format). Filters by publication date.
`public_end_time`	No	Patent publication end year (yyyy format). Filters by publication date.
`authority`	No	Patent authority code (e.g., CN, US, EP, JP). Filters by patent office. Use OR for multiple, e.g., "US OR EP".
`lang`	No	Language setting. Default is "en" (English). Choose "cn" (Chinese) or "en".

Implementation Reference

src/index.ts:224-230 (handler)

Handler function for the 'get_word_cloud' tool. Builds URL parameters from input arguments (with default lang='en'), and calls the shared PatSnap API helper for the 'word-cloud' endpoint.

async function getWordCloud(args: LangPatentArgs): Promise<ServerResult> {
  const params = buildCommonSearchParams(args);
  if (!args.lang) { // Add default lang if not provided
      params.append('lang', 'en');
  }
  return callPatsnapApi('word-cloud', params, 'get word cloud');
}

src/index.ts:318-324 (schema)

JSON input schema for language-aware patent tools including 'get_word_cloud'. Extends base schema with optional 'lang' field for English/Chinese.

const langPatentInputSchema = {
    ...basePatentInputSchema,
    properties: {
        ...basePatentInputSchema.properties,
        lang: { type: 'string', description: 'Language setting. Default is "en" (English). Choose "cn" (Chinese) or "en".' }
    }
};

src/index.ts:213-214 (schema)

TypeScript type definitions for input arguments. BasePatentArgs for common fields, LangPatentArgs extends it with optional 'lang' for tools like get_word_cloud.

type BasePatentArgs = { keywords?: string; ipc?: string; apply_start_time?: string; apply_end_time?: string; public_start_time?: string; public_end_time?: string; authority?: string };
type LangPatentArgs = BasePatentArgs & { lang?: string };

src/index.ts:342-345 (registration)

Tool registration in the ListTools handler. Defines name, description, and references the input schema.

  name: 'get_word_cloud',
  description: 'Obtain a snapshot of frequently occurring keywords/phrases from the most recent 5,000 published patents. Identify common terms for refining searches. Returns up to 100 keywords. Either keywords or IPC classification must be specified.',
  inputSchema: langPatentInputSchema
},

src/index.ts:395-395 (registration)
Maps the tool name 'get_word_cloud' to its handler function in the dispatch object used by CallToolRequest handler.
```
'get_word_cloud': getWordCloud,
```

Tool Definition Quality

A3.9/5.0

Behavior3/5

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

With no annotations provided, the description carries full burden. It discloses key behavioral traits: scope limitation (most recent 5,000 patents), output limit (up to 100 keywords), and requirement for either keywords or IPC. However, it doesn't mention rate limits, authentication needs, error conditions, or what happens when neither parameter is provided. The description adds value but lacks comprehensive behavioral context.

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 perfectly concise with three sentences that each earn their place: first states purpose and scope, second explains usage context, third specifies parameter requirements. No wasted words, well-structured, and front-loaded with the core functionality.

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

Completeness3/5

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

Given 8 parameters with full schema coverage but no annotations and no output schema, the description provides adequate but incomplete context. It covers the tool's purpose, scope, and parameter requirements well, but lacks information about return format, error handling, or performance characteristics that would be helpful for an agent invoking this tool.

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%, so the schema already documents all 8 parameters thoroughly. The description adds minimal parameter semantics beyond the schema - it only reinforces that 'Either keywords or IPC classification must be specified' and mentions the 5,000 patent scope. This meets the baseline 3 when schema does the heavy lifting.

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: 'Obtain a snapshot of frequently occurring keywords/phrases from the most recent 5,000 published patents' with specific scope (5,000 patents) and output (up to 100 keywords). It distinguishes from siblings by focusing on keyword analysis rather than citation counts, litigation data, trends, or other patent metrics.

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 description provides clear context for when to use this tool: 'Identify common terms for refining searches.' It specifies that either keywords or IPC classification must be specified, which is crucial guidance. However, it doesn't explicitly contrast when to use this versus alternatives like get_patent_trends or get_most_cited_patents for different analytical needs.

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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