scholar-mcp

Get Author

get_author

Read-only

Fetches a Semantic Scholar author profile and paginated publications by numeric author ID, or searches by name and returns up to five candidate authors for disambiguation.

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.

A direct lookup returns one page of publications, limit long from offset; next_offset is present when more follow. Semantic Scholar can list fewer publications than paperCount, so the last page may end short of that count.

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

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

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

Behavior5/5

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

Goes well beyond the readOnly/openWorld annotations: it discloses pagination semantics (limit/offset, next_offset presence), the caveat that Semantic Scholar may list fewer publications than paperCount so the last page can end short, and the long-running fallback that returns a job handle to poll with get_job_result. That last point is critical operational knowledge an agent could not infer from the annotations.

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-loads the core behavior in the first line, then branches cleanly into direct-lookup and pagination detail. The paperCount caveat is slightly tangential but genuinely useful, so nothing is seriously wasteful.

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?

An output schema exists so return values needn't be explained, and the description covers the remaining ambiguities: the two modes, candidate count, pagination, and the async job-handle fallback. Nothing an agent needs to 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 100%, so the baseline is 3; the description adds meaning by explaining that identifier's format determines which mode runs and that limit/offset apply only to direct ID lookup, reinforcing the intent behind the parameters rather than merely restating them.

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 and resource (fetch author profile and publications) plus a second mode (search by name), and the opening sentence names the dual behavior so an agent can tell it apart from a pure search tool like search_papers.

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?

Explicitly states the branch condition: numeric-looking identifier means direct ID lookup, otherwise a name search returning up to 5 candidates for disambiguation. It does not name sibling alternatives (e.g. resolve_standard_identifier for other ID types) to route to, which keeps it short of a 5.

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