mcp-pubmed

Instructions

Implementation Reference

• main.py:542-585 (handler)

  The get_related_articles tool handler implementation. It uses NCBI's elink API to fetch similar articles.

  @mcp.tool()
  async def get_related_articles(pmid: str, max_results: int = 10) -> str:
      """Find PubMed articles related to a given article.
  
      Uses NCBI's "similar articles" algorithm (co-citation and text similarity).
  
      Args:
          pmid: The PubMed ID of the reference article.
          max_results: Number of related articles to return (1-50, default 10).
  
      Returns:
          A ranked list of related articles with brief metadata.
          Returns an error message if the PMID is invalid or not found.
      """
      pmid = pmid.strip()
      if not pmid.isdigit():
          return _err(f"Invalid PMID: {pmid!r}. A PMID must be a numeric string.")
  
      max_results = max(1, min(max_results, 50))
  
      try:
          link_resp = await _get(
              "elink.fcgi",
              {
                  "dbfrom": "pubmed",
                  "db": "pubmed",
                  "id": pmid,
                  "cmd": "neighbor_score",
                  "retmode": "json",
              },
          )
  
          link_data = link_resp.json()
          related_pmids: list[str] = []
  
          try:
              for linkset in link_data.get("linksets", []):
                  for lsdb in linkset.get("linksetdbs", []):
                      if lsdb.get("linkname") == "pubmed_pubmed":
                          related_pmids = [
                              str(lid)
                              for lid in lsdb.get("links", [])
                              if str(lid) != pmid
                          ][:max_results]