scholar-mcp

Enrich Paper

enrich_paper

Read-only

Fetch OpenAlex metadata to enrich paper records with affiliations, funders, open access status, and concepts using the paper's DOI from Semantic Scholar.

Instructions

Fetch OpenAlex metadata to supplement Semantic Scholar data.

Resolves the paper's DOI from S2, then queries OpenAlex for the requested enrichment fields. Results are cached for 30 days.

A cached record answers immediately. Should the lookup run long it continues in the background and returns a job handle to poll with get_job_result.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`fields`	Yes	One or more of: affiliations, funders, oa_status, concepts.
`identifier`	Yes	S2 paper ID or DOI (prefix ``DOI:``).

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

Changed4 schema fields changedv1.10.0Sep 8, 2026
- addedOutput schema / additionalProperties
```
Added value: +true
```
- removedOutput schema / properties
```
Removed value: -{
-  "result": {
-    "type": "string"
-  }
-}
```
- removedOutput schema / required
```
Removed value: -[
-  "result"
-]
```
- removedOutput schema / x-fastmcp-wrap-result
```
Removed value: -true
```
First observedv1.9.0Aug 10, 2026

TDQS

A4.6/5.0

Behavior4/5

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

Annotations already indicate read-only and non-destructive behavior; the description adds useful details about caching and background job handling. It does not disclose potential rate limits or failure modes, 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.

Conciseness5/5

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

Three concise sentences cover purpose, resolution, caching, and async behavior without redundancy. The structure is focused and easy to parse.

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?

Given the output schema exists, the description adequately covers what the agent needs: input semantics, behavior, and async result retrieval. No critical context appears missing.

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?

Both parameters are fully described in the schema, with identifier format and valid field options explicitly listed. The description reinforces identifier semantics by mentioning DOI resolution.

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?

Clearly states the tool fetches OpenAlex metadata to supplement Semantic Scholar data, using a specific verb and resource. The distinction from siblings like get_paper and search_papers is evident through the OpenAlex enrichment focus.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Describes the enrichment purpose and the asynchronous behavior with get_job_result, giving practical usage context. It could more explicitly contrast with nearby tools like get_paper, but the enrichment scope is clear enough.

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