bioRxiv/medRxiv/arXiv preprint full text as structured sections for AI agents + search.
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io.github.genecell/preprint-fulltext is an MCP server that bioRxiv/medRxiv/arXiv preprint full text as structured sections for AI agents + search. Its tool list has not been published yet over stdio, sse and http, requires no API key, and scores 79/100 on MCPpedia's security, maintenance and efficiency rubric.
Config is the same across clients — only the file and path differ.
{
"mcpServers": {
"preprint-fulltext": {
"env": {
"CONTACT_EMAIL": "you@example.org"
},
"args": [
"--from",
"preprint-fulltext",
"preprint-fulltext-mcp"
],
"command": "uvx"
}
}
}Are you the author?
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Retrieve the full text of bioRxiv / medRxiv / arXiv preprints as clean, structured, embedding-ready data — from a CLI, a Python library, or an MCP server.
Run this in your terminal to verify the server starts. Then let us know if it worked — your result helps other developers.
uvx 'preprint-fulltext' 2>&1 | head -1 && echo "✓ Server started successfully"
After testing, let us know if it worked:
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No known CVEs.
Checked preprint-fulltext against OSV.dev.
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Retrieve the full text of bioRxiv / medRxiv / arXiv preprints as clean, structured, embedding-ready data — from a CLI, a Python library, or an MCP server.
preprint-fulltext turns a DOI (or a search) into structured sections
(abstract / introduction / methods / results / discussion), a single JSON/Markdown
document, or a chunked JSONL/Parquet corpus ready for embeddings and RAG. openRxiv
text-and-data-mining (TDM) compliance is enforced structurally, not left to the user.
"Embedding-ready" means the output is clean, section-aware, token-bounded chunks — ready to feed to your embedding model. Computing embeddings is an optional last step you own; this tool does not bundle an embedding model.
Preprint full text is scattered across incompatible channels: Europe PMC serves JATS
XML for the open-access subset, the openRxiv S3 buckets hold the authoritative
.meca corpus (requester-pays), OpenAlex is a catalog with n-gram-only full-text
search, and the bioRxiv/medRxiv websites render HTML. preprint-fulltext unifies
them behind one canonical data model and one shared JATS parser, so you get the
same structured output no matter where a document came from.
SKILL.md) that need to pull a preprint's
full text or search the literature mid-task.Language models and agents reason far more reliably over a paper's methods and results
than over its abstract alone — most scientific claims, protocols, quantities, and caveats
live in the body. preprint-fulltext gives Claude, Codex, and other agents that body as
clean, section-labeled, provenance- and license-tagged text, which is the substrate for
grounded scientific reasoning and deep research:
Because every Section/Chunk carries its kind (m