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h-lu

Paper Search MCP Server

by h-lu

search_arxiv

Search for preprints across physics, mathematics, computer science, and more on arXiv, a major open-access preprint server. Returns paper details for immediate access to full-text PDFs.

Instructions

Search preprints on arXiv - major open-access preprint server.

USE THIS TOOL WHEN:
- Searching for PREPRINTS (not peer-reviewed yet)
- You need free, immediate access to full-text PDFs
- Searching in: Physics, Mathematics, Computer Science, Statistics,
  Quantitative Biology, Quantitative Finance, Electrical Engineering

NOTE: arXiv is a PREPRINT server - papers may not be peer-reviewed.
For peer-reviewed papers, use search_crossref or search_semantic.

WORKFLOW:
1. search_arxiv(query) -> get paper_id (e.g., '2106.12345')
2. download_arxiv(paper_id) -> get PDF (always available)
3. read_arxiv_paper(paper_id) -> get full text as Markdown

Args:
    query: Search terms in any supported field.
    max_results: Number of results (default: 10).

Returns:
    List of paper dicts with: paper_id, title, authors, abstract, 
    published_date, pdf_url, categories.

Example:
    search_arxiv("quantum computing error correction", max_results=5)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
max_resultsNo
Behavior4/5

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

With no annotations, the description carries the burden. It discloses that arXiv contains preprints not yet peer-reviewed, and implies PDF availability via download_arxiv. It does not mention rate limits or auth, but adds value beyond schema.

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?

Well-structured with sections, concise sentences, and an example. Every part adds value without redundancy.

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?

Covers purpose, conditions, workflow, parameters, and return structure. Lacks mention of sorting or pagination, but given the tool's simplicity, it is mostly complete.

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 description coverage is 0%, so description compensates by describing query as 'Search terms in any supported field' and max_results as 'Number of results (default: 10)', plus an example. It could be more detailed on query syntax, but adequate.

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 it searches preprints on arXiv, a major open-access preprint server. It distinguishes from sibling search tools by specifying the content type and referencing the workflow with related tools.

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?

Explicitly lists when to use this tool (searching for preprints, need free full-text, specific fields) and when not to (peer-reviewed papers, directing to search_crossref or search_semantic). Provides clear alternatives.

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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