crossref-mcp
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@crossref-mcpfind the paper with DOI 10.1038/nature12373"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
crossref-mcp
Crossref REST API を使って学術文献のメタデータを取得する MCP サーバーです。
機能 (Tools)
Tool | 説明 |
| DOI から1件の文献メタデータを取得します。 |
| フリーテキスト / タイトル / 著者から文献を検索します。 |
取得・検索結果には、タイトル・著者・掲載誌・出版年・DOI・被引用数・(提供されていれば)アブストラクトなどが含まれます。
Related MCP server: CrossRef MCP Server
実行 (uvx)
公開リポジトリから直接実行できます:
uvx --from git+https://github.com/ebiyu/crossref-mcp crossref-mcpローカルのクローンから実行する場合:
uvx --from . crossref-mcpMCP クライアントへの登録
Claude Desktop / Claude Code などの mcpServers 設定例:
{
"mcpServers": {
"crossref": {
"command": "uvx",
"args": ["--from", "git+https://github.com/ebiyu/crossref-mcp", "crossref-mcp"],
"env": {
"CROSSREF_MAILTO": "you@example.com"
}
}
}
}ローカルにクローンしたものを使う場合は、--from に絶対パスを指定します(Windows の例):
{
"mcpServers": {
"crossref": {
"command": "uvx",
"args": [
"--from",
"PATH_TO_THIS_FOLDER",
"crossref-mcp"
],
"env": {
"CROSSREF_MAILTO": "you@example.com"
}
}
}
}macOS / Linux の場合は "/path/to/crossref-mcp" のように指定してください。
Claude Code の CLI から登録する場合:
claude mcp add crossref -e CROSSREF_MAILTO=you@example.com -- uvx --from git+https://github.com/ebiyu/crossref-mcp crossref-mcpレート制限の尊重
Crossref の アクセスポリシー に従い、自動でリクエスト間隔を調整します。
レスポンスの
X-Rate-Limit-Limit/X-Rate-Limit-Intervalヘッダから許容レートを学習し、間隔 ÷ 上限秒ずつリクエストを空けます。リクエストは直列化され、同時実行数の上限も超えません。429 Too Many Requestsを受けた場合はRetry-Afterを尊重し、なければ指数バックオフ(最大30秒、最大5回)で再試行します。
CROSSREF_MAILTO(推奨)
環境変数 CROSSREF_MAILTO にメールアドレスを設定すると、Crossref の
"polite pool"
が使われ、より安定したレスポンスが得られます。設定は任意です。
開発
uv sync
uv run crossref-mcp # stdio でサーバー起動ライセンス
MIT
Available Tools
2 toolsget_work_by_doiA
Retrieve bibliographic metadata for a single work by its DOI.
Args: doi: The Digital Object Identifier, e.g. "10.1145/3292500.3330701". A full URL such as "https://doi.org/10.1145/..." is also accepted.
Returns: A dictionary of the work's metadata (title, authors, journal, year, DOI, abstract when available, citation counts, etc.).
| Name | Required | Description | Default |
|---|---|---|---|
| doi | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description is fully responsible for behavioral disclosure. It explains accepted DOI formats and the returned dictionary fields, which is useful, but it does not mention error behavior, missing metadata, or any side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three concise, front-loaded sections with no wasted words. The purpose is stated first, followed by args and returns, both of which earn their place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter lookup tool, the description provides enough context: what the tool does, what the parameter expects, and what the return value contains. The output schema exists, so return-value detail in the description is a bonus.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but the description fully documents the single doi parameter with a concrete example, the full URL alternative, and its role. This adds substantial meaning beyond the mere property name 'Doi'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb+resource: 'Retrieve bibliographic metadata for a single work by its DOI.' It clearly differentiates from the sibling search_works by emphasizing single-work lookup via DOI rather than general search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The context is clear: use this when you have a DOI and need metadata for one specific work. It stops short of explicitly naming alternatives or saying when not to use it, but the single-work framing implicitly distinguishes it from search_works.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_worksA
Search Crossref for works by free text, title, and/or author.
At least one of query, title, or author must be provided.
Args: query: Free-text bibliographic search across all fields. title: Restrict the search to the work's title. author: Restrict the search to author names. rows: Number of results to return (1-50, default 5).
Returns:
A dictionary with total_results and a works list of metadata
dictionaries, each in the same shape as get_work_by_doi.
| Name | Required | Description | Default |
|---|---|---|---|
| rows | No | ||
| query | No | ||
| title | No | ||
| author | No |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It explains the return structure (dictionary with total_results and works list), the row limit (1-50), and the requirement for at least one query parameter. This goes beyond the minimal description, although it doesn't discuss potential errors or side effects (though 'Search' implies read-only).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded with the main action. It uses a concise one-sentence summary, a necessary constraint note, a tight argument list, and a clear returns section. No wasted words or redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (4 parameters, no annotations), the description covers all essential aspects: what it does, parameter semantics, required input conditions, and return format. It references get_work_by_doi for the shape of result items, which is sufficient given the output schema exists. The description is complete and self-contained.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides no descriptions (0% coverage), but the description thoroughly explains each parameter: query (free-text across all fields), title (restrict to title), author (restrict to author names), and rows (number of results with range and default). It also clarifies that at least one of query/title/author must be provided, which is not evident from the schema alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description begins with 'Search Crossref for works by free text, title, and/or author,' which clearly states the action (search) and resource (Crossref works). It also specifies the search facets, distinguishing it from the sibling tool get_work_by_doi, which retrieves a single work by DOI.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use the tool ('Search Crossref for works'), and the constraint 'At least one of query, title, or author must be provided' gives a clear prerequisite. However, it does not explicitly mention alternatives or when not to use it, such as contrasting with get_work_by_doi when a DOI is known.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
2 tool updates
v0.1.0- First observed
get_work_by_doi - First observed
search_works
TDQS
The two tools are clearly distinct: one retrieves a specific work by DOI, the other searches for works using query parameters. There is no overlap in their purposes, making it easy for an agent to select the appropriate tool.
Both tools follow a consistent verb_noun pattern: 'get_work_by_doi' and 'search_works'. The naming clearly indicates the action and the resource, and there is no mixing of conventions.
With only two tools, the server feels thin for a general Crossref API, but for the narrow purpose of retrieving works by identifier or search, it is minimally sufficient. The count is at the low end of what is reasonable.
The core workflows of looking up a work by DOI and searching for works are covered. Minor gaps exist, such as no support for other identifiers or listing all works of an author directly, but the primary use cases are addressed.
Maintenance
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