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Semantic Scholar Papers Search

semanticscholar.papers.search
Read-onlyIdempotent

Search 200M+ academic papers by title and abstract text across all fields of study. Returns Semantic Scholar paper ID, DOI, title, year, venue, authors, citation count, and open-access PDF link when available. Complements openalex.works_search (broader topic classification) with Semantic Scholar's AI-driven relevance ranking and TLDR summaries. Call semanticscholar.get_paper with a result paper_id, DOI, or ArXiv ID for full detail including abstract and TLDR. Data: api.semanticscholar.org, no auth required.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoNumber of results to return (1-25, default 10)
queryYesSearch query across paper title and abstract (e.g. "transformer attention")

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNoPresent only when the call failed. Includes error code, message, request_id, and any provider-specific extras.
resultNoTool response payload. Shape varies per tool — consult the tool description and inputSchema. May be an object, array, string, or number depending on the upstream provider response.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already cover readOnly, openWorld, idempotent, and non-destructive traits, so the safety profile is handled. The description adds practical details beyond annotations: 'Data: api.semanticscholar.org, no auth required' and the conditional 'open-access PDF link when available,' which are not in the annotations and give useful context. There is no contradiction with 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?

The description is organized into five distinct sentences covering purpose, returned fields, sibling comparison, follow-up tool, and source/auth. Each sentence carries information and the main purpose is front-loaded. It is slightly longer than minimal but not verbose, and the structure aids scanning.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has an output schema, so return structure is not a gap, and the description already lists the key fields. It covers the search scope, returned fields, a sibling comparison, a follow-up tool, and auth/source details. The only minor omission is pagination or limit behavior, but the schema documents the limit parameter, so it is sufficiently complete.

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?

Schema description coverage is 100%, so both query and limit are fully documented in the schema. The description only adds that search is over 'title and abstract text,' which slightly elaborates the query field but is already implied by the schema example ('transformer attention'). No significant additional meaning is provided beyond the schema, so the baseline 3 is appropriate.

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 action: 'Search 200M+ academic papers by title and abstract text across all fields of study.' It specifies the resource (papers), the scope (title/abstract, all fields), and lists the returned fields. It also explicitly distinguishes itself from the sibling openalex.works_search, so an agent can tell them apart without opening schemas.

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?

The description explicitly names openalex.works_search as a complementary alternative, explaining that it offers 'broader topic classification' while this tool provides 'AI-driven relevance ranking and TLDR summaries,' giving clear selection guidance. It also instructs to 'Call semanticscholar.get_paper with a result paper_id...' for full detail, defining a follow-up path. However, it does not mention other academic search siblings like education.papers.search or crossref.works.search, so exclusions are partial.

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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