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space-finder-mcp

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uk_stac_search

Search UK EO DataHub satellite and climate data via STAC by keyword, collection, bounding box, or date range. Returns catalog summaries and structured JSON for public datasets, no authentication required.

Instructions

英国 EO DataHub の衛星・気候データをSTACで検索する（公開カタログは認証不要）。

例:「英国の気候モデルデータ」「UKのSentinel画像」
content に表示用サマリ、structuredContent に JSON（id/日時/bbox/コレクション）を返す。

Args:
    collection: コレクションID（例 "sentinel2_ard", "ukcp"）。省略で全コレクション。
    query: キーワード検索（例 "climate", "sentinel"）。
    bbox: 空間範囲（"lon_min,lat_min,lon_max,lat_max"）。
    datetime: 時間範囲（"YYYY-MM-DD" または "start/end"）。省略で最新。
    limit: 返す件数（既定 5、最大 10）。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bboxNo
limitNo
queryNo
datetimeNo
collectionNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.25.2

TDQS

A3.6/5.0
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 does disclose that auth is not required for the public catalog, and describes the return shape (content summary + structuredContent JSON with id/datetime/bbox/collection). However it omits rate limits, error behavior, and pagination nuances of the STAC API.

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 purpose sentence, followed by examples, return-shape note, and a compact Args block. Efficient and well organized, though the Japanese/English mix and slightly redundant example lines keep it from a 5.

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?

Given a 5-parameter search tool with no annotations and no output schema, the description covers purpose, examples, auth requirement, return format, and all parameter semantics. It could still state behavior on empty results or rate limits, but the essentials are present.

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 — and it does well: it explains each of the five parameters with examples, formats (bbox as lon_min,lat_min,lon_max,lat_max; datetime as YYYY-MM-DD or start/end), defaults, and limits (limit default 5, max 10). This is strong value beyond the bare schema.

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?

Description states a specific verb and resource (STAC search of UK EO DataHub satellite/climate data) and gives example queries. It doesn't explicitly differentiate itself from the many sibling search tools (stac_search, copernicus_search, eodashboard_detail), which is a missed opportunity given the dense sibling set.

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?

Usage is implied via examples ('英国の気候モデルデータ', 'UKのSentinel画像') and notes that the public catalog needs no auth, but there is no when-to-use-vs-alternatives guidance among the many sibling search tools. Adequate but with a clear gap.

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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