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deeparchi-ai

Patent MCP Server

by deeparchi-ai

batch_get_patents

Retrieve full details for multiple patents in one request, avoiding repeated single-patent calls. Accepts up to 20 publication numbers and returns PatentDetail objects.

Instructions

Get full details for multiple patents in a single call. Much faster than calling get_patent N times separately. Returns list of PatentDetail objects. Max 20 patents per call.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
publication_numbersYesPatent publication numbers (e.g. CN110286864A)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.9.2

TDQS

A4/5.0
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 the hard limit of 20 patents per call and the return type, but says nothing about what happens on exceeding the limit, error/failure handling for invalid publication numbers, or permission requirements.

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?

Three short sentences, all earning their place: purpose, sibling comparison, return shape, and limit. The core value proposition (batch speed) is front-loaded.

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?

For a one-parameter batch read with no output schema, the description covers purpose, return type, and the batch ceiling. Minor gaps remain around limit-exceeded behavior and failure handling, but nothing an agent needs in order to invoke it correctly is missing.

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?

There is a single parameter with 100% schema description coverage, including an example format (CN110286864A), so the schema already documents it fully. The description adds only the implicit constraint that the array size is capped at 20, which is baseline-level value.

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?

States a specific verb and resource ('Get full details for multiple patents in a single call') and explicitly distinguishes itself from the sibling get_patent by framing the batch operation as faster than N separate calls. It also names the return shape (list of PatentDetail objects).

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?

It gives clear usage context by contrasting with get_patent N times and states the batch ceiling (max 20 per call), which tells the agent when this is the right choice. It stops short of an explicit when-not rule (e.g. prefer get_patent for a single lookup).

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