BioPython MCP Server

Create a formatted literature review from PubMed search results and write to MD file.

This function searches PubMed, fetches article metadata, formats it as markdown with complete abstracts, and writes the content directly to a file. The LLM determines both the storage location and filename.

Args: query: PubMed search query (supports full Entrez syntax including year filters) Example: "BRCA1 AND breast cancer AND 2020:2024[PDAT]" path: Relative directory path within vault (e.g., "research/cancer" or "genetics/reviews") The LLM decides the directory structure. filename: Name of the markdown file (e.g., "brca1_review_2024.md" or "alport_syndrome.md") The LLM decides the filename. Should include .md extension. obsidian_vault: Path to Obsidian vault root (optional, defaults to OBSIDIAN_VAULT_PATH env variable) Example: "/Users/user/Documents/MyVault" max_results: Maximum number of articles to include (default: 25, max: 1000) sort: Sort order - "pub_date", "relevance", etc. (default: "pub_date")

Returns: Dictionary with review results and metadata: - status: "success" or "error" - filepath: Full path where file was written - articles_found: Total number of articles found - articles_written: Number of articles successfully processed - articles_with_pmc: Count of articles with PMC IDs - articles_with_doi: Count of articles with DOIs - query: Original search query - file_size_kb: File size in kilobytes - year_range: {"min": int, "max": int} - top_journals: List of top 5 journals by article count - execution_time_seconds: Time taken to generate review

Examples: >>> # Using environment variable for vault path >>> result = pubmed_review( ... query="COL4A3[Gene] AND Alport syndrome", ... path="genetics/reviews", ... filename="alport_syndrome_2024.md" ... )

Notes: - Vault path comes from OBSIDIAN_VAULT_PATH environment variable or obsidian_vault parameter - LLM controls both directory structure (path) and filename separately - Writes markdown file directly to disk with complete abstracts - Fetches articles in batches of 20 (NCBI limit) - Respects NCBI rate limits (3/sec or 10/sec with API key) - For very large reviews (>500 articles), consider splitting into multiple calls - Includes Obsidian-compatible YAML frontmatter