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h-lu

Paper Search MCP Server

by h-lu

read_semantic_paper

Access open-access academic paper full text from Semantic Scholar as a fallback when arXiv or Sci-Hub are not viable. Input a paper ID to receive Markdown output.

Instructions

Read paper via Semantic Scholar (open-access only, use as LAST RESORT).

DOWNLOAD PRIORITY (try in order):
1. If arXiv paper -> use read_arxiv_paper(arxiv_id)
2. If published before 2023 -> use read_scihub_paper(doi)
3. Use this tool as last resort

Args:
    paper_id: Semantic Scholar ID or prefixed ID (DOI:, ARXIV:, PMID:).
    save_path: Directory to save PDF.

Returns:
    Full paper text in Markdown format.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paper_idYes
save_pathNo
Behavior3/5

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

No annotations provided, so description carries full burden. It notes open-access only and returns Markdown text, but lacks details on failure modes, rate limits, or why it's a last resort beyond a simple statement.

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?

Well-structured with clear sections (DOWNLOAD PRIORITY, Args, Returns). Purpose is front-loaded. One small efficiency: the priority list is slightly verbose but essential for guidance.

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?

Given no annotations and no output schema, the description covers purpose, priority rule, arguments, and return format. It's sufficient for an agent to decide when to use and how to call, though more on fallback behavior would improve completeness.

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 0%, so description must compensate. The Args section explains paper_id accepts various prefixed IDs and save_path for directory, but doesn't elaborate on formats or behavior when save_path is null.

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 reads a paper via Semantic Scholar and is open-access only. It distinguishes from siblings by providing a download priority list that names alternative tools and conditions.

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 says 'use as LAST RESORT' and gives a prioritized list with specific conditions (arXiv vs. pre-2023), telling the agent exactly when to use this tool versus 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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