PyEuropePMC

PyEuropePMC is a Python client for Europe PMC. It searches the literature, downloads open-access full text, and parses JATS XML into metadata, plain text and structured sections. It also ships a command-line tool and an MCP server for AI agents.

✨ Features

• Europe PMC search with plain queries or a fluent QueryBuilder, pagination, and results as JSON, XML or Dublin Core. Search guide
• Ten more sources in one search, with duplicates merged: PubMed, arXiv, ClinicalTrials.gov, OpenAlex, Semantic Scholar, CORE, DBLP, DOAJ, HAL and Zenodo. Semantic Scholar needs the semanticscholar extra and CORE an API key. Multi-source search
• Full text: XML (Europe PMC first, then other open sources), PDF and HTML, plus bulk PDF downloads from the Europe PMC FTP site. Full-text retrieval
• JATS XML parsing: metadata, authors, tables, figures and references; plain text and Markdown; typed sections for retrieval-augmented generation (RAG); JATS normalization and BioC export. XML parsing, JATS normalization
• Text-mining annotations for genes, diseases, chemicals and their relationships. Examples
• Citations and metadata: walk citation graphs, and enrich records from Crossref, Unpaywall, OpenAlex, Semantic Scholar, DataCite, ORCID, ROR and iCite. Citation walking, Enrichment
• Analysis: pandas DataFrames, citation statistics, duplicate detection, plots, and PRISMA-style search logs for systematic reviews. Analytics, Review tracking
• RDF knowledge graphs from parsed articles, mapped by the rdf_map.yml that ships with the package; pass RDFMapper(config_path=...) or PipelineConfig(rdf_config_path=...) to use your own. Data models and RDF
• A command line and an MCP server, described below.

📦 Installation

pip install pyeuropepmc                              # core
pip install "pyeuropepmc[analytics,visualization]"   # add extras (quote the brackets)
pip install "pyeuropepmc[all]"                       # every optional feature

PyEuropePMC supports Python 3.10 to 3.13. The core install covers search, full-text download, XML parsing, RDF, the command line and the MCP server. The extras add:

Upgrading from 1.x? The migration guide lists what moved into extras.

🚀 Quick start

from pyeuropepmc import FullTextClient, FullTextXMLParser, QueryBuilder, SearchClient

# 1. Search Europe PMC for open-access articles ("CRISPR AND OPEN_ACCESS:y")
query = QueryBuilder().keyword("CRISPR").and_().field("open_access", True).build()
with SearchClient() as search:
    hits = search.search_and_parse(query, pageSize=10)
pmcid = next(hit["pmcid"] for hit in hits if hit.get("pmcid"))

# 2. Download the article's JATS XML (raises an error if no source has it)
with FullTextClient() as fulltext:
    xml_path = fulltext.download_xml_by_pmcid(pmcid, output_path=f"articles/{pmcid}.xml")

# 3. Parse it
parser = FullTextXMLParser(xml_path.read_text(encoding="utf-8"))
metadata = parser.extract_metadata()
print(metadata["title"])
print(", ".join(metadata["authors"][:3]))
text = parser.to_plaintext()  # or parser.to_markdown()

# 4. Collect text blocks with their section path, ready to chunk and embed for RAG
chunks = []
for section in parser.get_full_text_sections_structured():
    if section["section_type"] not in ("front", "body"):  # skip back matter and appendices
        continue
    for block in section["content"]:
        if block.get("text"):
            path = section.get("section_path", section["title"])
            chunks.append({"section": path, "type": block["type"], "text": block["text"]})
print(f"{len(chunks)} text blocks")

section_type is front for the title and abstract, then body, back or appendix. Each block has a type such as paragraph, list, table or figure. Tables and figures carry label and caption, and tables also carry rows. The XML parsing guide covers the other extractors.

🔒 Safe XML parsing

PyEuropePMC parses every XML document it reads with defusedxml: full-text articles, Europe PMC search results, arXiv and PubMed responses, and local files. A DOCTYPE declaration is accepted, but a document that declares entities, internal or external, is refused rather than expanded; FullTextXMLParser raises ParsingError. lxml is not used and does not need to be installed.

💻 Command line

pyeuropepmc unified_search search "CRISPR base editing" --limit 10 --output results.json
pyeuropepmc benchmark list-datasets

unified_search search queries Europe PMC, PubMed and arXiv unless you pass --source. Add --help to any command for its options.

🤖 MCP server

pyeuropepmc-mcp serves 24 tools over the Model Context Protocol: multi-source search, paper details and citations, citation-graph walking, ClinicalTrials.gov search, a local full-text index, figure extraction, bibliography conversion and LLM-powered analysis. The server is part of the core install. pip install "pyeuropepmc[all]" enables every tool; otherwise the bib_* tools need bibliography, and the LLM tools need agentic plus an OpenAI-compatible API key (see Configuration below).

pyeuropepmc-mcp                                # stdio, for Claude Desktop and similar clients
pyeuropepmc mcp                                # the same server, through the CLI
pyeuropepmc-mcp --transport streamable-http    # HTTP at http://127.0.0.1:8000/mcp

For Claude Desktop and other clients that start the server themselves: