Skip to main content
Glama

Get bioRxiv/medRxiv preprint details

biorxiv_get_preprint
Read-onlyIdempotent

Fetch a bioRxiv or medRxiv preprint's title, authors, abstract, versions, and journal publication status by DOI or URL. Accepts bare DOIs and links, auto-detects the server.

Instructions

Fetch a preprint by DOI from the official bioRxiv/medRxiv API: title, authors, category, license, abstract, every posted version with dates, and the published journal version if one exists. Accepts a bare DOI (10.1101/2024.01.01.573711), a doi.org link, or a biorxiv.org/medrxiv.org content URL (version suffix like v2 is honoured). Auto-detects the server unless server is given.

Input Schema

NameRequiredDescriptionDefault
doiYesPreprint DOI or URL
serverNoWhich server to query; omit to auto-detect

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, openWorld and non-destructive, so the safety bar is low; the description still adds real value by naming the authoritative upstream API and disclosing version-suffix handling and server auto-detection. Gaps remain on rate limits, not-found behavior for an invalid DOI, and error shape, which matter for an open-world network call.

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

Conciseness5/5

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

Two dense sentences with zero filler: the payload contents lead, and input-format and auto-detection rules follow. Nothing is repeated and nothing is buried.

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?

With only two parameters and no output schema, the definition covers what an agent needs: accepted inputs, server resolution, and the shape of the returned record. The only omissions are failure modes for an unresolvable or malformed DOI, which are minor for a simple read 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?

Schema coverage is 100%, so both parameters are already documented and the baseline is 3. The description adds concrete format examples for `doi` and notes that a trailing version suffix is honoured, which is genuine semantics beyond "Preprint DOI or URL", but the `server` behavior is simply a restatement of the 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?

States a specific verb and resource ("Fetch a preprint by DOI from the official bioRxiv/medRxiv API") and enumerates exactly what comes back: title, authors, category, license, abstract, versions, published journal version. It never names a sibling, though, so an agent must infer that this is the metadata lookup rather than the full-text (biorxiv_get_full_text), search, or listing tool.

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?

The description spells out accepted input forms (bare DOI, doi.org link, content URL with v2 suffix) and the auto-detect-unless-`server`-given rule, which is useful orientation. It gives no explicit when-to-use guidance relative to biorxiv_search or biorxiv_get_full_text, leaving the selection to inference from the name.

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