GPSS Patent Search MCP

tool_search_patents_tools_search_patents_post

Search GPSS patents by keywords and optional filters to retrieve patent numbers, titles, abstracts, and inventor details for prior-art or patent research.

Instructions

MCP Tool endpoint for patent search.

This tool searches the GPSS (Global Patent Search System) for patents matching your keywords. Authentication is handled automatically via the USER_CODE environment variable.

Simply provide your search keywords and optional filters. The tool will:

Automatically read USER_CODE from the environment
Send the request to GPSS API
Return parsed results with patent numbers, titles, abstracts, and inventor info

Responses:

200 (Success): Successful Response
- Content-Type: application/json
- Response Properties:
- Example:

{
  "success": true,
  "data": "unknown_type",
  "request_params": "unknown_type"
}

422: Validation Error
- Content-Type: application/json
- Response Properties:
- Example:

{
  "detail": [
    "unknown_type"
  ]
}

Input Schema

TableJSON Schema

Name	Required	Description	Default
`keywords`	Yes	Keyword expression understood by GPSS (e.g., '雲端 AND 轉型')
`databases`	No	Optional list of GPSS database codes (patDB)
`max_results`	No	Maximum number of results to request from GPSS
`patent_types`	No	Optional list of GPSS patent type codes (patTY)
`search_field`	No	Which GPSS field group(s) to search. Provide a single value or a list to reuse the same keywords across multiple fields (additional fields are combined with OR per GPSS API rules). Supported values include single fields such as: title, abstract, claims, patent_number, publication_date, application_number, application_date, applicant_name, first_applicant_name, applicant_country, first_applicant_country, inventor_name, inventor_country, agent_name, examiner, priority, priority_date, ipc, first_ipc, cpc, first_cpc, loc, fi, f_term, d_term, uspc, and cited_patents.	title
`application_types`	No	Optional list of GPSS application type codes (patAG)
`publication_date_to`	No	Upper bound for publication date (YYYYMMDD)
`publication_date_from`	No	Lower bound for publication date (YYYYMMDD)

Output Schema

TableJSON Schema

Name	Required	Description	Default
`data`	No
`error`	No
`success`	Yes
`request_params`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.3Sep 27, 2026

TDQS

B3.3/5.0

Behavior3/5

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

No annotations are provided, so the description carries the full burden. It usefully discloses that authentication is automatic via the USER_CODE environment variable and lists the step sequence (read env, call GPSS, parse results), plus the 200/422 response codes. It omits rate limits, pagination behavior, and what happens if USER_CODE is unset.

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

Conciseness3/5

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

The opening two paragraphs are tight and front-loaded, but the bulk of the description is an auto-generated response block whose examples are placeholder junk ('data': 'unknown_type'), adding length without value since an output schema already exists.

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?

A full output schema covers return values and the description explains the auth flow, so the core is covered. But for an 8-parameter search tool it lacks guidance on discovering valid database/patent-type codes via the sibling tools and says nothing about result volume or failure modes beyond 422.

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 baseline is 3. The description only says 'keywords and optional filters' and adds nothing about search_field semantics, date formats, or how multiple search_fields are OR-combined beyond what the schema already documents.

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 specific verb+resource: 'searches the GPSS (Global Patent Search System) for patents matching your keywords.' An agent can tell what the tool returns (patent numbers, titles, abstracts, inventor info). However, it never names the sibling tools (get_available_databases, get_search_examples) or explains how it differs from them, so it stops short of full differentiation.

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?

'Simply provide your search keywords and optional filters' implies the basic call pattern, but there is no when-to-use vs. when-not guidance and no mention that database/type codes should come from the sibling lookup tools. Usage is implied rather than explicitly scoped.

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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