mcp-crossref

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find_related_works

Identify papers bibliographically similar to a seed DOI by shared title vocabulary and subjects, returning relevance-scored works for 'more like this' discovery without references or citations.

Instructions

Find works bibliographically similar to a given paper (same title vocabulary and subjects).

When to use:
    - "More like this" from one good paper, without needing its references or citations.

Args:
    doi: DOI of the seed paper.
    rows: Number of similar works to return (1-50, default 10).

Returns:
    {"seed": compact work, "related": [compact work + relevance_score]}

Tip: snowball_doi gives citation-based neighbours (references, citing works, OpenAlex related),
which are usually more meaningful than text similarity.

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

A4.6/5.0

Behavior4/5

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

No annotations, so the description carries the full burden: it discloses the similarity mechanism (text vocabulary/subjects rather than citations) and the response shape (seed + related works with relevance_score). It does not cover failure modes such as an unresolvable DOI or rate limiting, but the core behavioral context is present.

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?

Front-loaded one-line purpose followed by clearly labelled When to use / Args / Returns / Tip blocks. The Returns section is somewhat redundant given an output schema exists, but it is short and no sentence is 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 2-parameter read tool with an output schema, the description covers purpose, triggering scenario, parameter meaning, return shape, and the key sibling alternative. Nothing an agent needs to select or invoke it correctly is missing.

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

Parameters4/5

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 identified as the seed paper's identifier and rows is explained with a range (1-50) and default (10) that the bare schema does not express. Field titles alone would not have told an agent any of this.

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 (find) and resource (works bibliographically similar) and pins down the similarity basis ('same title vocabulary and subjects'), which cleanly separates it from citation-based siblings like snowball_doi.

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?

Explicit 'When to use' scenario ('More like this' from one good paper, without needing references or citations) plus a Tip that names snowball_doi as the alternative and says when it is usually more meaningful. Both the when and the when-not are stated.

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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