skills/43-wentorai-research-plugins/skills/literature/fulltext/pmc-ftp-bulk-download/SKILL.md
Bulk download PMC Open Access articles via FTP for large-scale mining
npx skillsauth add brycewang-stanford/Awesome-Agent-Skills-for-Empirical-Research pmc-ftp-bulk-downloadInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
The PMC FTP Service provides bulk download access to millions of full-text articles from PubMed Central's Open Access Subset. Unlike the single-article APIs (E-utilities, BioC), the FTP service is designed for large-scale corpus construction — downloading entire collections for text mining, NLP training, systematic reviews, and bibliometric analysis. Free, no authentication required.
Note: PMC is migrating to AWS-based Cloud Service in August 2026. FTP paths may change; check official docs for updates.
# FTP (classic)
ftp ftp.ncbi.nlm.nih.gov
# Navigate to: /pub/pmc
# HTTPS alternative (recommended)
# Base: https://ftp.ncbi.nlm.nih.gov/pub/pmc/
| Dataset | Path | Content | Format |
|---------|------|---------|--------|
| OA Commercial | /pub/pmc/oa_comm/ | CC BY/CC0 articles (commercial use OK) | .tar.gz packages |
| OA Non-Commercial | /pub/pmc/oa_noncomm/ | CC BY-NC articles | .tar.gz packages |
| OA Other | /pub/pmc/oa_other/ | Other open licenses | .tar.gz packages |
| Author Manuscripts | /pub/pmc/manuscript/ | NIH-funded manuscripts | .tar.gz packages |
| Historical OCR | /pub/pmc/historical_ocr/ | Pre-digital scanned articles | .tar.gz |
| File lists | /pub/pmc/oa_file_list.csv | Index of all OA articles | CSV |
Download the master index to plan your downloads:
# Download the OA file list (CSV, ~200MB)
wget https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_file_list.csv
# CSV columns:
# File, Article Citation, AccessionID, LastUpdated, PMID, License
import requests
import tarfile
import io
import csv
def download_article_package(pmcid: str, base_url: str = "https://ftp.ncbi.nlm.nih.gov/pub/pmc"):
"""Download and extract a specific PMC article package."""
# First, look up the file path from the file list
# (In practice, you'd load this once and index by PMCID)
file_list_url = f"{base_url}/oa_file_list.csv"
# ... lookup pmcid in file list to get path ...
# Download the tar.gz package
resp = requests.get(f"{base_url}/{file_path}", stream=True)
resp.raise_for_status()
# Extract
with tarfile.open(fileobj=io.BytesIO(resp.content), mode="r:gz") as tar:
tar.extractall(path=f"./articles/{pmcid}")
print(f"Extracted {pmcid}")
#!/bin/bash
# Download all commercial-use articles (CC BY / CC0)
# WARNING: This is ~100GB+ compressed
mkdir -p pmc_corpus/commercial
cd pmc_corpus/commercial
# Download the baseline (all current articles)
wget -r -np -nH --cut-dirs=3 \
https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_comm/xml/
# Incremental updates (run periodically)
wget -r -np -nH --cut-dirs=3 -N \
https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_comm/xml/
import csv
import requests
from pathlib import Path
def download_filtered_corpus(file_list_path: str, output_dir: str,
license_filter: str = "CC BY",
max_articles: int = 1000):
"""Download articles matching a license filter."""
output = Path(output_dir)
output.mkdir(parents=True, exist_ok=True)
base = "https://ftp.ncbi.nlm.nih.gov/pub/pmc"
downloaded = 0
with open(file_list_path) as f:
reader = csv.DictReader(f)
for row in reader:
if license_filter and license_filter not in row.get("License", ""):
continue
if downloaded >= max_articles:
break
file_path = row["File"]
url = f"{base}/{file_path}"
local_path = output / Path(file_path).name
if local_path.exists():
continue
resp = requests.get(url, stream=True, timeout=60)
if resp.status_code == 200:
local_path.write_bytes(resp.content)
downloaded += 1
if downloaded % 100 == 0:
print(f"Downloaded {downloaded} articles...")
print(f"Total downloaded: {downloaded}")
Convert between different article identifiers:
# PMID → PMCID → DOI conversion
curl "https://www.ncbi.nlm.nih.gov/pmc/utils/idconv/v1.0/?ids=29346600&format=json"
# Batch conversion (up to 200 IDs)
curl "https://www.ncbi.nlm.nih.gov/pmc/utils/idconv/v1.0/?ids=29346600,30266829,31048553&format=json"
Each article package (.tar.gz) typically contains:
PMC1234567/
├── PMC1234567.xml # Full text in JATS XML
├── PMC1234567.pdf # PDF (if available)
├── figure1.jpg # Figures
├── figure2.jpg
├── table1.html # Tables (sometimes)
└── supplement1.pdf # Supplementary materials
oa_file_list.csv first and filter locally-N flag to only get new/updated filestools
Recommend AND run open-source AI tools, agents, Claude Code / Codex skills, and MCP servers for any stage of a literature review — searching, reading, extracting, synthesizing, screening, citation-checking, and paper writing. Use when the user asks "what tool should I use to..." OR "install/run/use <tool> to ..." for research/lit-review work: automating a survey or related-work section, PDF→Markdown extraction for LLMs (MinerU/marker/docling), PRISMA / systematic review (ASReview), citation-backed Q&A over PDFs (PaperQA2), wiring papers into Claude/Cursor via MCP (arxiv/paper-search/zotero servers), or chatting with a Zotero library. Ships a launcher (scripts/litrun.py) that installs each tool in an isolated venv and runs it. Curated catalog of 70+ vetted projects. 支持中英文(用于「文献综述工具选型」与「一键安装/运行」)。
development
Route empirical-research requests through the Auto-Empirical Research Skills catalog when this whole repository is installed as one skill in Codex, CodeBuddy, Claude Code, or another IDE. Use to choose and load the right vendored AERS skill for causal inference, econometrics, replication, data acquisition, manuscript writing, peer review and referee responses, citation checking, de-AIGC editing, or full empirical-paper workflows without reading the entire repository at once.
documentation
Use when the project collects primary data or runs a field, lab, or survey experiment, before the intervention begins — write the pre-analysis plan, size the sample from a power calculation, and register with the AEA RCT Registry. Apply after the design is chosen in aer-identification and before any outcome data are seen.
tools
Guide economists to authoritative data sources with explicit, confirmed data specifications before retrieval; interfaces with Playwright MCP to navigate portals and extract real data, not articles about data.