Get a specific paper from CrossRef by its DOI.
Args:
doi: Digital Object Identifier (e.g., '10.1038/nature12373').
Returns:
Paper metadata in dictionary format, or empty dict if not found.
Example:
get_crossref_paper_by_doi("10.1038/nature12373")
| Name | Required | Description | Default |
|---|---|---|---|
| doi | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses the return format ('dictionary format') and behavior when not found ('empty dict'), backed by a concrete example. It could add details about potential errors or rate limits, but the core behavior is transparent.
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 with clearly labeled Args, Returns, and Example sections. Every sentence adds value, and there is no redundancy or fluff.
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 simple one-parameter tool, the description covers the full essential context: purpose, parameter semantics, return type, and not-found behavior, plus a usage example. It is complete enough without an output schema.
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 only the parameter name 'doi', but the description adds a meaningful explanation with an example ('10.1038/nature12373'). This compensates well for the 0% schema coverage, though it does not discuss malformed or missing DOI handling.
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 clearly states 'Get a specific paper from CrossRef by its DOI', using a specific verb and resource. This distinguishes it from sibling tools like search_crossref (for searching) and download_crossref (for downloading).
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 usage when a DOI is already known, but does not explicitly mention when not to use it or point to alternatives such as search_crossref for finding papers without a DOI. The context of sibling tools partially fills this gap.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Multiple tools appear to serve the same purpose, such as search_arxiv and search-arxiv, or papers-search-basic, paper-search-advanced, search_papers, and search. The download/read tools for different sources follow similar patterns, but some return 'not supported' messages, making it unclear which tools are actually functional.
Tool names mix snake_case, kebab-case, and bare verbs without a consistent pattern. For example, about_nanci, analysis-citation-network, download-full-paper-arxiv, fetch, and search_arxiv all coexist, and the same action for different sources alternates conventions (search-arxiv vs search_arxiv).
With 53 tools, the server is heavily over-scoped. Many tools are redundant or near-duplicates, such as six source-specific search tools plus an aggregate search, and the inclusion of both paper and clinical trial tools in one server creates unnecessary bloat.
The server covers a wide range of research workflows, including search, download, read, citations, authors, and clinical trials. However, several tools (crossref/pubmed download/read) are non-functional dead ends, and the redundancy makes it harder to navigate the surface.