scholar-mcp

Get Author

get_author

Read-only

Fetch an author's profile and publications by entering their numeric ID or name. Disambiguates name searches by returning up to 5 candidate authors to select from.

Instructions

Fetch author profile and publications, or search by name.

If identifier looks like a numeric S2 author ID, fetches the author directly. Otherwise performs a name search and returns up to 5 candidates for disambiguation.

Answers directly in normal use. Should the call 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
`limit`	No	Publications per page (only used for direct ID lookup).
`offset`	No	Publication page offset (only used for direct ID lookup).
`identifier`	Yes	S2 author ID (numeric string) or free-text author name.

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

A4.7/5.0

Behavior5/5

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

The description discloses the asynchronous behavior: normal calls answer directly while long-running calls return a job handle to poll with get_job_result. It also mentions the up-to-5 candidate fallback for name searches, going beyond the readOnly/destructive annotations.

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?

The description is concise and well-structured: purpose first, then identifier behavior, then execution/async behavior. No unnecessary wording.

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?

With an output schema present, the description does not need to detail return fields. It covers the main call behavior, name-search disambiguation, pagination-relevant parameters, and the background job fallback, making it complete for the tool's complexity.

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 100%, and the top-level description adds the conditional meaning of identifier: numeric S2 author ID triggers direct fetch, otherwise name search. The limit/offset descriptions already clarify they only apply to direct ID lookups.

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?

The description clearly states the tool fetches an author profile and publications or searches by name, and it explains the identifier-based branching behavior. This distinguishes it from paper/book/standard siblings.

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?

It provides clear context on when direct fetch versus name-search disambiguation is used, but it does not explicitly compare with alternative tools for author-related queries. Still, the guidance is unambiguous and actionable.

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