Skip to main content
Glama

jp_lit_get_record

Retrieve detailed bibliographic records and official URLs from Japanese literature databases including NDL, CiNii, J-STAGE, and others. Returns metadata only, excluding full text and images.

Instructions

文献レコード詳細を取得する。source=national_archives / jacar は目録メタデータと公式レコードURLを返し、画像本体・IIIF・OCR本文は取得しない。source=nijl_articles は国文学論文DBのHTMLから書誌メタデータと公式レコードURLを best-effort で返し、本文・PDF・OPAC追跡は取得しない。source=kokusho は国書DBのJSONから書誌・著作・所在・公式URL・manifest URL 等のメタデータを返し、manifest 本体・画像・OCR は取得しない。source=ninjal_bibliography は日本語研究・日本語教育文献DBのHTMLから書誌メタデータと本文リンクURLを best-effort で返し、本文自体は取得しない。source=ndl_digital の場合、source_metadata.next_digital_library.available=true であれば jp_lit_get_text_coordinates / jp_lit_get_fulltext / jp_lit_search_pages が利用可能。false の場合は OCR 系ツールを利用できない。実務上は次世代側未収録であることが多いが、現実装ではアクセス制限等との厳密な区別はしていない。個人送信対象など、MCP から自動全文取得できなくても NDL ログインや参加館・館内端末で手動閲覧できる導線は content_access.manual_viewing を確認する

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sourceYes検索・取得・記録対象の情報源ID。jp_lit_search の結果や source plan に含まれる source を指定する。
source_idYessource 内のレコードID。jp_lit_search の items[].source_id を指定する。
force_refreshNotrue の場合はローカル cache を使わず upstream API から再取得する。false の場合は保存済み cache を優先する。

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
rawYes
urlYes
cacheNo
titleYes
extentYes
sourceYes
authorsYes
summaryYes
languageYes
subjectsYes
subtitleYes
issued_atYes
publisherYes
source_idYes
identifiersYes
availabilityYes
journal_titleYes
material_typeYes
title_readingYes
content_accessYes
issued_at_labelYes
source_metadataYes
publication_placeYes
table_of_contentsYes
alternative_titlesYes
issued_at_precisionYes
Behavior4/5

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

With no annotations, the description fully discloses behavior: best-effort for some sources, conditional availability for OCR tools, and data source details. It mentions that access restrictions are not strictly differentiated. Slightly more detail on side effects (none) would improve, but it's highly transparent.

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?

The description is lengthy but necessary to cover multiple sources and their specific behaviors. The first sentence is a clear summary. Some restructuring into bullet points could improve readability, but overall the information is well-organized and earned.

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 the complexity and variability across sources, the description covers return types, constraints, and cross-tool dependencies. With an output schema present, the lack of detailed output structure is acceptable. It could be slightly more complete regarding error cases, but it is comprehensive for an MCP tool.

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?

The input schema already provides 100% coverage with descriptions for all three parameters. The tool description does not add significant new information about parameter semantics beyond what the schema offers. Baseline 3 is appropriate.

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?

The description clearly states the tool's purpose: retrieving detailed records for a given source. It specifies what is returned per source (metadata, URLs) and what is not (images, fulltext, OCR), distinguishing it from sibling tools like jp_lit_get_fulltext and jp_lit_search.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit guidance for each source, including when to use alternative tools. For ndl_digital, it indicates when jp_lit_get_text_coordinates or jp_lit_get_fulltext are available. It also notes limitations like best-effort retrieval for nijl_articles and manual viewing for personal delivery items.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/itarunnn/jp-lit-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server