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hsiangjenli

GPSS Patent Search MCP

by hsiangjenli

tool_get_databases_tools_get_available_databases_post

Retrieve available patent databases from the Global Patent Search System (GPSS), including region, database code, and description, to identify which collections can be queried.

Instructions

MCP Tool endpoint for getting available databases.

Responses:

  • 200 (Success): Successful Response

    • Content-Type: application/json

    • Response Properties:

      • databases: Mapping of region -> database code -> description. Each database entry is a human-friendly description derived from the PatDB enum.

    • Example:

{
  "success": true,
  "databases": {
    "key": "value"
  }
}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
successYes
databasesYesMapping of region -> database code -> description. Each database entry is a human-friendly description derived from the `PatDB` enum.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.3

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full disclosure burden. 'Getting' weakly implies a read-only, side-effect-free operation, but it says nothing about auth requirements, caching, rate limits, or whether results are static. Almost all text is spent restating the response shape rather than behavioral traits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The sentence of actual purpose is front-loaded, but the bulk of the description is a verbose response-schema dump (status codes, content types, sample JSON) that is redundant given the output schema exists. Much of the text does not earn its place.

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?

For a no-parameter read tool with an output schema, the core operation is understandable, but the description omits any usage framing or behavioral notes and instead duplicates return-value structure that the output schema already covers. Adequate but with clear gaps.

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?

The tool takes zero parameters, so the baseline is 4. There is nothing to document, and the description correctly avoids inventing parameter semantics.

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?

States a clear verb+resource: 'getting available databases'. An agent can tell it retrieves the list of databases, distinct from the sibling search_patents/get_search_examples tools. It does not explicitly name or differentiate from those siblings, and the 'MCP Tool endpoint' phrasing is meta noise rather than added meaning.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives no indication of when to use this tool versus alternatives, nor any precondition (e.g. 'call this first to discover valid database codes before searching patents'). Usage must be entirely inferred.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.