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h-lu

Paper Search MCP Server

by h-lu

search_pubmed

Search PubMed for peer-reviewed biomedical research papers. Retrieve metadata including PMID, title, abstract, authors, DOI, and publication date. Use for drug studies, clinical trials, and disease research.

Instructions

Search biomedical literature on PubMed (NCBI database).

USE THIS TOOL WHEN:
- Searching for medical, clinical, or biomedical research
- You need peer-reviewed published papers (not preprints)
- Searching for drug studies, clinical trials, disease research

DOMAIN: Medicine, Biology, Pharmacology, Public Health, 
Clinical Research, Genetics, Biochemistry.

LIMITATION: PubMed provides metadata/abstracts ONLY, not full PDFs.

WORKFLOW FOR FULL TEXT:
1. search_pubmed(query) -> get DOI from results
2. download_scihub(doi) -> download PDF (if published before 2023)

Args:
    query: Medical/scientific terms (e.g., 'cancer immunotherapy', 'COVID-19 vaccine').
    max_results: Number of results (default: 10).

Returns:
    List of paper dicts with: paper_id (PMID), title, authors, 
    abstract, published_date, doi, url.

Example:
    search_pubmed("CRISPR gene therapy", max_results=5)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
max_resultsNo
Behavior5/5

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

With no annotations provided, the description fully discloses behavioral traits: limitation to metadata/abstracts, a suggested workflow for full text, and the return format (list of paper dicts with specific fields). It is transparent about what the tool does and does not do.

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 well-organized with sections (USE THIS TOOL WHEN, DOMAIN, LIMITATION, WORKFLOW) and bullet points. Every sentence provides essential information with no redundancy or fluff.

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 the tool has 2 parameters, no output schema, and no annotations, the description is highly complete. It covers purpose, usage guidelines, limitations, workflow integration, parameter details, return format, and an example. No gaps remain for an agent to select and invoke correctly.

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

Parameters5/5

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

Schema description coverage is 0%, so the description must compensate. It explains the query parameter with examples (e.g., 'cancer immunotherapy') and specifies max_results as number of results with default 10. An example usage is also provided, adding clarity beyond the schema.

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 biomedical literature on PubMed, specifies the database, and includes domain fields. It distinguishes from siblings like search_arxiv and search_medrxiv by naming PubMed and biomedical focus.

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?

The 'USE THIS TOOL WHEN' section explicitly lists appropriate use cases (medical research, peer-reviewed papers) and includes a limitation (metadata only) and a workflow for full text using download_scihub. This provides clear when-to-use and when-not-to-use guidance.

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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