Skip to main content
Glama

search_papers

Search academic papers across multiple sources by query and filter by year, author, journal, or platform to locate relevant research.

Instructions

Search academic papers from multiple sources including arXiv, Web of Science, etc.

Input Schema

NameRequiredDescriptionDefault
daysNoNumber of days to search back (bioRxiv/medRxiv only)
yearNoYear filter (e.g., "2023", "2020-2023", "2020-")
queryYesSearch query string
authorNoAuthor name filter
sortByNoSort results by relevance, date, or citations
journalNoJournal name filter
categoryNoCategory filter (e.g., cs.AI for arXiv)
platformNoPlatform to search (default: crossref). Options: arxiv, webofscience/wos, pubmed, biorxiv, medrxiv, semantic, iacr, googlescholar/scholar, scihub, sciencedirect, springer, scopus, crossref, openalex, or all. "all" uses the unified multi-source path; prefer search_literature for seed-aware workflows. Note: Wiley only supports PDF download by DOI, use download_paper instead.
sortOrderNoSort order: ascending or descending
maxResultsNoMaximum number of results to return
fetchDetailsNoFetch detailed information (IACR only)
fieldsOfStudyNoFields of study filter (Semantic Scholar only)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.8/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden and does not meet it. It says nothing about whether results are metadata-only or full text, whether multi-source results are deduplicated or ranked, rate limits, auth requirements, or pagination — the "etc." leaves the actual source set undefined.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

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

A single short sentence with no waste, but it is brief to the point of under-specification, and the trailing "etc." is filler that conveys no information. Front-loading is fine; the content is just thin for a 12-parameter aggregator.

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

Completeness2/5

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

For a 12-parameter, multi-platform tool with no annotations and no output schema, the description is far too sparse. An agent cannot tell what comes back, how sources are merged, or how this tool relates to the large family of single-platform and workflow siblings.

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 all 12 parameters are already documented in the schema, including enum values, defaults, and per-platform caveats. The description adds no parameter meaning beyond that, which is the baseline expectation rather than a failure.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ("Search academic papers") and claims multi-source coverage. However, it does not distinguish this tool from the many per-platform siblings (search_arxiv, search_pubmed, search_crossref, etc.), and the multi-source framing is at odds with a platform parameter that defaults to a single source (crossref).

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

Usage Guidelines2/5

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

No when-to-use guidance at all: nothing says when to use this generic search versus the platform-specific siblings, nor when to pass platform="all" versus a single source. The only routing hint ("prefer search_literature for seed-aware workflows") lives in the schema, not the description.

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