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kmaneesh

BioPython MCP Server

by kmaneesh

entrez_summary

Retrieve lightweight document summaries from NCBI Entrez databases to access key metadata quickly without downloading full records, ideal for efficient metadata queries in bioinformatics workflows.

Instructions

Get document summaries (DocSums) from NCBI Entrez.

Document summaries are lightweight alternatives to full records, containing key metadata without the full content. Much faster for metadata-only queries.

Args: database: Database name (e.g., 'pubmed', 'gene', 'clinvar', 'nucleotide') ids: Single ID, comma-separated string, or list of IDs use_cache: Whether to use cached results (default: True, TTL: 7 days)

Returns: Dictionary containing: - summaries: List of document summary dictionaries - ids: List of IDs requested - count: Number of summaries returned - database: Database queried - cached: Whether result was from cache (if use_cache=True)

Examples: >>> entrez_summary("pubmed", "12345678") >>> entrez_summary("gene", ["672", "7157"]) # BRCA1, TP53 >>> entrez_summary("clinvar", "12345") >>> entrez_summary("nucleotide", "NM_000207,NM_001127")

Notes: - Much faster than entrez_fetch for metadata-only queries - Fields returned vary by database type - Rate limited to 3 req/sec (or 10 req/sec with API key) - Use this instead of fetch when you don't need full sequence/text - Cached results have 7 day TTL since summary data is relatively static

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
databaseYes
idsYes
use_cacheNo

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