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space-finder-mcp

by loosephoto
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Python
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reverse_lookup

Find the first or record space objects by category and country using Wikidata. Answers queries like 'Which country launched the first space telescope?'

Instructions

逆引き歴史Q&A — カテゴリ+国 で絞り込んだ最初/記録の宇宙オブジェクトを Wikidata から探す。

例: 「米国で最初に打ち上げた宇宙望遠鏡は?」→ category="宇宙望遠鏡", country="United States"
例: 「日本初の人工衛星は?」→ category="人工衛星", country="Japan"

Args:
    category: 探す対象のカテゴリ（宇宙望遠鏡/space probe/satellite/astronaut など）。
    launch_date: 打ち上げ日(P619)で並べる場合は True。False にすると対象を列挙する。
    country: 国名（例 "United States", "Japan", "India"）。Wikidata 上で Q-id に自動解決する。
    country_qid: 国の Q-id を直接指定する場合（例 "Q30"=米国, "Q17"=日本）。country より優先。
    limit: 返す件数（既定 5）。
    order: "asc"=古い順(最初のもの), "desc"=新しい順。
    language: ラベル表示言語（ja/en/zh など）。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
orderNoasc
countryNo
categoryYes
languageNoja
country_qidNo
launch_dateNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.25.2
    • changedOutput schema / (root)
      Previous value: -{
-  "properties": {
-    "result": {
-      "title": "Result",
-      "type": "string"
-    }
-  },
-  "required": [
-    "result"
-  ],
-  "title": "reverse_lookupOutput",
-  "type": "object"
-}New value: +null
  2. First observedv0.1.0

TDQS

A4.1/5.0
Behavior3/5

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

With no annotations, the description must carry the full behavioral burden. It discloses the Wikidata source, that launch_date=True sorts by launch date while False lists objects, and that country_qid takes priority over country. However, it omits read-only nature, permissions, rate limits, error behavior, and return structure.

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 front-loaded with purpose, then examples, then an Args block. Every part earns its place: the examples illustrate usage and the Args block compensates for the zero schema description coverage.

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 7-parameter lookup with no annotations and no output schema, the description covers all inputs and key behavioral details. It is nearly complete, but it does not describe the return shape or what fields the Wikidata results contain, which matters because no output schema is provided.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must explain all parameters. It does: category with examples, launch_date sorting vs listing, country with example values and auto Q-id resolution, country_qid priority, limit default, order asc/desc meaning, and language for labels.

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?

The description states a specific verb+resource: reverse-looking up first/record space objects from Wikidata filtered by category and country, with concrete examples. It is clear what the tool does, though it does not explicitly differentiate itself from the many sibling search/lookup tools.

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 examples ('米国で最初に打ち上げた宇宙望遠鏡は?' → category/country) clearly establish when to use the tool for historical 'first/record' queries. It gives no explicit exclusions or named alternatives among siblings, but the context is clear enough.

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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