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SuyashEkhande

PubMed Advanced MCP Server

pubmed_search

Search PubMed for biomedical literature and retrieve abstracts, authors, MeSH terms, and more using natural language or advanced syntax.

Instructions

Search PubMed for biomedical literature.

Searches 34M+ PubMed abstracts using natural language or E-utilities syntax. Returns publication metadata including titles, abstracts, authors, and MeSH terms.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesSearch query (e.g., "CRISPR gene therapy", "cancer AND 2023[dp]")
filtersNoOptional filters: - publication_date_start/end: Date range (YYYY or YYYY-MM-DD) - publication_types: ["Review", "Clinical Trial", etc.] - language: "eng", "spa", etc. - free_full_text_only: Limit to free articles
sort_byNo"relevance", "pub_date", or "first_author"relevance
max_resultsNoNumber of results (1-10000)
use_historyNoStore for pipeline chaining
include_abstractNoInclude abstracts in results

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

No annotations are provided, so the description carries the burden. It discloses the search scope (34M+ PubMed abstracts), query syntax flexibility, and return content (metadata including abstract and MeSH terms). This adds meaningful behavioral context beyond the schema, though it omits details like rate limits or pagination.

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 extremely concise: two short sentences plus a one-liner about return content. Every sentence provides distinct value, and the core purpose is front-loaded in the first sentence.

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?

For a search tool with an output schema and full parameter documentation, the description is sufficient. It clearly states what it does, what it searches, and what it returns. It lacks explicit alternative guidance, but that is covered under usage guidelines. Overall, complete enough for an agent to invoke correctly.

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 100%, so baseline is 3. The description adds value by explaining that the query can be natural language or E-utilities syntax, which goes beyond the schema's examples. It also notes return fields like MeSH terms, aiding expectation of parameter impact.

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?

The description clearly states the tool 'Search PubMed for biomedical literature', which is a specific verb+resource. It distinguishes from siblings like pmc_search by explicitly naming PubMed, but does not explicitly differentiate from other search tools like advanced_search or global_search.

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 provides clear context that this tool is for searching biomedical literature. It mentions support for natural language or E-utilities syntax, implying flexible usage, but does not explicitly state when not to use it or suggest alternative tools.

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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