scholar-mcp

Search Papers

search_papers

Read-only

Search academic papers by query, filtering by year, venue, citations, and field of study. Returns sorted results with pagination.

Instructions

Search Semantic Scholar for papers matching a query.

Usually completes in a few seconds.

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	Default
`sort`	No	Sort order — relevance, citations, or year.	relevance
`limit`	No	Maximum results to return (max 100).
`query`	Yes	Keyword or semantic search query.
`venue`	No	Filter by venue name.
`fields`	No	Field set preset — compact, standard, or full.	compact
`offset`	No	Pagination offset.
`year_end`	No	Latest publication year (inclusive).
`year_start`	No	Earliest publication year (inclusive).
`min_citations`	No	Minimum citation count.
`fields_of_study`	No	Filter by fields, e.g. ["Computer Science"].

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

A4.5/5.0

Behavior4/5

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

The annotations already convey read-only and non-destructive behavior, and the description adds useful behavioral detail about latency and asynchronous fallback. It does not mention error cases, but the async and timing disclosure is meaningful beyond 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.

Conciseness5/5

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

The description is brief and to the point, with no redundant or filler content. Each sentence serves a purpose: identifying the action, setting latency expectations, and explaining the async path.

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 that an output schema exists and the annotations cover safety flags, the description provides enough context for correct invocation. The async behavior is the only non-obvious operational aspect, and it is explicitly covered.

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

Parameters3/5

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

All parameters are described in the schema, so the baseline applies; the description itself adds little parameter-level detail beyond saying the search matches 'a query.' The schema already covers sort, filters, pagination, and field presets adequately.

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 searches Semantic Scholar for papers matching a query. It also distinguishes the normal direct response from the long-running fallback, making the tool's core purpose obvious relative to siblings like get_paper or search_books.

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?

It explicitly tells callers that the call usually completes in a few seconds and that long-running requests return a job handle to poll via get_job_result. This gives clear, actionable guidance on expected behavior and how to handle async results.

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