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space-finder-mcp

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Python
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csa_dataset_search

Search the Canadian Space Agency open data portal for datasets by keyword and return matching dataset details; no authentication required.

Instructions

CSA（カナダ宇宙庁）オープンデータポータルでデータセットを検索する（認証不要）。

例:「カナダのRADARSATデータ」「CSAの宇宙データセット」
content に表示用サマリ、structuredContent に JSON（ID/タイトル/概要/ライセンス/URL）を返す。

Args:
    query: 検索語（例 "radarsat", "space", "earth observation"）。省略で先頭のデータセット。
    limit: 返す件数（既定 10、最大 20）。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.25.2

TDQS

A3.8/5.0
Behavior4/5

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 no authentication is required and describes the return shape (display summary in content, JSON with ID/title/summary/license/URL in structuredContent). It omits pagination behavior beyond limit and any rate-limit notes, but for a read-only public search endpoint this is solid disclosure.

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

Conciseness4/5

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

Front-loaded with the purpose, then examples, then return format, then args. Reasonably tight, though the example-query block and Args listing add some repetition that could be trimmed.

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 2-parameter, no-annotation, no-output-schema tool, the description covers purpose, auth, parameters, defaults, limits, and return structure. An agent has enough to call it correctly; only explicit sibling routing is missing.

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?

Schema description coverage is 0%, so the description must compensate. It documents both parameters: query's meaning and example terms plus the omission behavior (returns leading datasets), and limit's default of 10 with a maximum of 20 — the max is not in the schema, so this adds real value.

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 and resource ('search datasets' on the CSA open data portal) plus example queries, which is clearer than a bare name. However, with ~40 sibling search tools it never names or contrasts an alternative (e.g. jaxa_dataset_search, copernicus_search), so differentiation relies on the reader noticing the agency name.

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?

Gives example queries and notes 認証不要 (no auth needed), which implies the usage context. It does not say when to prefer this over the many other dataset-search siblings or state any exclusion conditions.

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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