mcp-crossref

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snowball_doi

Find a paper's references, citing works, and related research from its DOI to conduct citation snowballing, including open-access status and abstracts.

Instructions

Citation snowballing around one paper: its references (backward), the works that cite it
(forward), and related works, plus open-access status and an abstract when available.

Forward citations are not available from Crossref, so this tool uses OpenAlex (free; set
OPENALEX_API_KEY for a 10x daily budget, otherwise it runs keyless).

When to use:
    - Systematic literature review snowballing from one or two seed papers.
    - "Who built on this paper?", "what newer work cites it?", "is there a free PDF?"

Args:
    doi: DOI of the seed paper.
    rows: Works per direction, sorted by citation count (1-50, default 10).

Returns:
    {"seed": work with open_access + abstract, "backward_total", "backward": [...],
     "forward_total", "forward": [...], "related": [...],
     "strong_candidates": works found by more than one direction}

Notes:
    - OpenAlex matching is automatic and occasionally wrong; sanity-check odd entries.
    - open_access.url is a legal free copy when OpenAlex knows one; DOI != free PDF.
    - Costs about 4 OpenAlex list calls; single lookups are free.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`doi`	Yes
`rows`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Oct 3, 2026

TDQS

A5/5.0

Behavior5/5

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

With no annotations provided, the description carries the full burden and delivers: it discloses the OpenAlex dependency, the OPENALEX_API_KEY budget behavior (10x daily budget vs keyless), per-call cost (~4 list calls), automatic matching that is 'occasionally wrong', and the non-obvious fact that open_access.url is a legal free copy while DOI != free PDF.

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?

Front-loaded with a one-line summary, then cleanly sectioned into When to use / Args / Returns / Notes. It is longer than average but every block (provider rationale, cost, matching caveat) adds distinct value with no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a multi-source traversal tool, the description covers provider, cost, caveats, args, and the concrete return shape (seed, backward/forward totals, strong_candidates). Even with an output schema present, the returned-key summary is useful and everything an agent needs to call it correctly is present.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description must compensate, and it does: 'doi' is defined as the seed paper's DOI and 'rows' is given the semantics 'works per direction, sorted by citation count (1-50, default 10)' — including the range and sort order absent from the schema.

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?

States a specific verb (citation snowballing) and resource (one seed paper) and enumerates the three traversal directions (backward/forward/related). It also names the underlying provider distinction (OpenAlex for forward citations, since Crossref lacks them), which separates it from siblings like find_related_works and get_crossref_references.

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 'When to use' block gives both a scenario (systematic literature review snowballing from seed papers) and concrete user-style questions it answers. An agent can route to this tool without guessing.

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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