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From research-data chaos to focused research feeds

Paperzilla monitors new papers, datasets, software repositories, patents, and research alerts, filters them against your research topic, ranks what matters, and delivers a structured feed to your inbox, app, RSS reader, CLI, MCP server, API, or AI research agent.
Create your research feed
Track papers from arXiv, bioRxiv, medRxiv, ChemRxiv, PubMed-indexed literature, forwarded Google Scholar alerts, and paper-related datasets, software repos, and patents.
System overview

Messy research streams in. Structured research feeds out.

Inputs
Relevance Engine
Outputs
Inputs
Papers, alerts, datasets, software, patents
arXiv
preprint
bioRxiv
preprint
medRxiv
preprint
ChemRxiv
preprint
PubMed
indexed literature
Scholar Alerts
email
Journal Alerts
email
Custom Sources
custom
Datasets*
data
Software Repos*
software
Patents*
patents
Paperzilla
Relevance Engine
Topic filter
Scoped to your research interest
Relevance ranking
Strongest matches rise first
Feedback loop
Learns what matters over time
improves over time
Outputs
Feeds and access for people, tools, and agents
Feed
App Feed
human
Mail
Email Digest
human
RSS
RSS / Atom
human
MCP
MCP Server
agent
>
CLI Access
agent
API
API Access*
agent
1
Connect sources
2
Tune relevance
3
Get focused feeds
Scattered papers, datasets, repositories, patents, and alerts go in. Paperzilla filters for relevance. Structured research feeds come out, ready for humans and AI agents. Items marked with * are paper-related datasets, software repos, patents, and API access.
The problem

Research updates are scattered everywhere

New research data does not arrive in one clean stream. Papers appear across preprint servers, datasets live in separate archives, software changes in repositories, patents surface elsewhere, and alerts arrive by email. Some updates are essential. Most are noise.
The more specific your research interest, the harder it becomes to maintain a feed that is broad enough to discover surprises but focused enough to be useful.
You shouldn't check 5+ sources every day
Scattered across arXiv, Scholar, datasets, repositories, patents, and journals
Keyword alerts miss the point
Too broad or too narrow, never just right
Manual curation doesn't scale
Fifty abstracts, records, and repository updates a week is not a research workflow
Agents need scoped context
Broad web search is noisy input for research tasks
How it works

One pipeline for continuous research monitoring

01
Input
Bring in the research streams
Paperzilla monitors papers from arXiv, bioRxiv, medRxiv, and ChemRxiv, plus PubMed-indexed biomedical and clinical literature, with paper-related datasets, software repos, and patents in the same workflow. Forward existing alerts directly into Paperzilla.
02
Relevance
Filter and rank by relevance
Each project defines what matters for a specific research topic. As papers and related research data arrive, Paperzilla filters and ranks them against that topic. The relevance engine improves over time using recommender-style feedback.
03
Output
Deliver structured output
The result is a focused research feed delivered how you work: daily or weekly email digests, in-app feed, RSS/Atom, MCP server access, CLI, and API access for agent workflows.
Built for everyone

Research feeds your team can read and your agents can use

Paperzilla is designed for both human review and automated research workflows. One filtered research data feed, consumed multiple ways.
R
For researchers & teams
Humans get less noise
✓ Read a focused research feed in the app
✓ Receive daily or weekly email digests
✓ Subscribe by RSS / Atom
✓ Stop manually checking scattered sources
AI
For AI agents & automation
Agents get better context
✓ Access topic-specific feeds through MCP
✓ Use CLI workflows for research automation
✓ Build recurring research-data briefings
✓ Give agents a current, filtered research stream
Use cases

What people build with Paperzilla

Features

What Paperzilla gives you

◎
Paper source intake
Monitors arXiv, bioRxiv, medRxiv, ChemRxiv, and new PubMed-indexed records, with additional sources on request.
▧
Research data intake
Paper-related datasets, software repos, and patents fit into the same relevance workflow.
✉
Forwarded alert intake
Forward Google Scholar or other alert emails directly into Paperzilla.
⊙
Topic-based filtering
Create a project around a research interest. Papers and related research data are filtered against it continuously.
↑
Relevance ranking
Strongest matches rise above adjacent or low-signal results automatically.
↻
Feedback-driven learning
The feed improves over time using recommender-style feedback on what matters.
▤
Human-readable delivery
In-app feed, daily or weekly email digests, or RSS/Atom subscription.
⌘
Agent-ready delivery
Expose the filtered feed through MCP server access, CLI, and API access for automated workflows.
Want the full feature list?View all features →
Get started

Build your first focused research feed

Choose a topic. Connect paper sources, alerts, and paper-related datasets, software repos, and patents. Let Paperzilla keep the feed current for you, your team, and your AI agents.
Create your research feed
View all features
Guided setup; takes less than 2 minutes
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