pubmed-stream: PubMed search and PubMed Central full-text download, for researchers and their AI assistants
pubmed-stream is an open-source Python library and command-line tool that takes a PubMed search to a knowledge graph of the literature. It is built on NCBI's official E-utilities API, works from the command line or Python, and needs nothing beyond requests. AI assistants use it too: it is a plugin for Claude Code and Codex, and a PubMed MCP server for them and Gemini CLI, so you can ask a research question in plain English and get an answer that cites only papers the assistant downloaded and read.
With it you can:
- Search PubMed and PubMed Central (PMC) with field tags and MeSH (Medical Subject Headings), and see how many papers a search finds before downloading anything (section 2)
- Bulk-download full-text articles from PubMed Central as JSON, with metadata, references and text or JATS XML, and the PubMed abstracts of articles without free full text (section 1)
- Export citations as BibTeX or RIS for Zotero, EndNote and Mendeley (section 1)
- Find the papers that cite a paper, the papers it cites and the papers PubMed rates as similar, with retracted papers, reviews and NIH funding flagged (section 3)
- Build a knowledge graph of a study's literature in Obsidian, one Markdown note per paper and MeSH concept, linked by citations, similarity and topics (section 4)
- Give AI assistants PubMed tools through the MCP server or the plugin, and summarize abstracts with a local LLM through Ollama, so nothing leaves your computer (section 5)
- Measure the impact of a retracted paper through the papers citing it and the papers citing those (tutorial 8)
Documentation: melhzy.github.io/pubmed-stream, the tutorials, guides and reference in one searchable website, with every notebook shown with its results.
A study made with it: the Aβ*56 retraction impact page, how a retracted Alzheimer's paper spread through the literature and how much of it language models learned, as an interactive page where every number comes from the study's files; see Studies.
New to programming? Start with tutorial 0, which takes a research question to a map of its literature in an afternoon. Click Open in Colab to run it in your web browser, with nothing to install; you only type your question into one settings cell.
flowchart LR
S["PubMed searches"] -->|"download"| D["Full-text articles<br/>metadata, references, text"]
K["Key papers"] -->|"neighborhood"| N["Similar, citing and cited papers<br/>flagged reviews, retractions, NIH funding"]
D --> G["Knowledge graph<br/>kg_topic, an Obsidian vault"]
N --> G
G --> O["Explore, write, refresh"]
Contents
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