PAPERZILLA

High-signal research paper feeds

The paper that

inspires

your

research was published this morning.

Did you see it?

10,000+ new papers appear every day

Paperzilla turns scattered paper sources and forwarded alerts into a relevance-ranked research feed, delivered to your inbox, app, RSS/Atom reader, CLI, MCP server, or AI agent.

Create a research feed

Guided setup; takes less than 2 minutes

System overview

From paper chaos to focused research context

Paperzilla brings together new papers and forwarded alerts, filters them against the research topics you care about, and turns them into structured feeds for researchers, teams, tools, and AI agents.

Inputs

Relevance Engine

Outputs

Inputs

Preprints, alerts, newsletters, custom sources

arXiv

preprint

bioRxiv

preprint

medRxiv

preprint

ChemRxiv

preprint

Scholar Alerts

Journal Alerts

Custom Sources

custom

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 for people, tools, and agents

Feed

App Feed

human

Mail

Email Digest

human

RSS

RSS / Atom

human

MCP

MCP Server

agent

CLI Access

agent

Connect sources

Tune relevance

Get focused feeds

Scattered papers and alerts go in. Paperzilla filters for relevance. Structured research feeds come out, ready for humans and AI agents.

How it works

How Paperzilla works

Paperzilla continuously monitors research sources, filters new papers against your topic, and delivers the results where your research workflow already happens.

Input

Connect sources and alerts

Harvest papers from preprint servers and forward existing paper alerts into Paperzilla. Bring the scattered streams into one place without rebuilding your monitoring setup from scratch.

Relevance

Filter and rank by relevance

Define the topic you care about. Paperzilla ranks incoming papers, separates must-reads from background noise, and improves over time with feedback and recommender-style signals.

Output

Send structured output anywhere

Read your feed in the app, receive daily or weekly email digests, subscribe with RSS/Atom, or connect agent workflows through MCP and CLI access.

Sources and alerts

Bring every paper stream into one relevance filter

Paperzilla can monitor preprint sources directly and accept forwarded paper-alert emails, so your feed can include both new papers from major servers and alerts you already rely on.

Preprint harvesting

Track new papers from major preprint servers without manually checking each source.

arXiv

bioRxiv

medRxiv

ChemRxiv

ChinaXiv

Forwarded alerts

Forward existing alerts to Paperzilla and let the relevance engine decide what belongs in your focused feed.

Google Scholar alerts

Paper alert emails

Journal alerts

Newsletter-style paper alerts

Custom sources

Need another source? Additional source support can be added on request.

Additional sources on request

Need another source? Let us know.

Built for everyone

Built for researchers, teams, and AI agents

Paperzilla does not lock your research feed into one interface. The same relevance-filtered stream can be read by people, shared with teams, or consumed by AI agents and automation workflows.

Human review

For researchers and teams

Skim the app feed, receive daily or weekly email digests, or subscribe through RSS/Atom. Stay current on narrow research topics without living in alerts, search pages, and source-specific inboxes.

In-app paper feed

Daily or weekly email digest

RSS/Atom feed

Topic-specific monitoring

Must-read and related-paper triage

Agent workflows

For AI agents and automation

Give research agents a current, scoped paper stream instead of asking them to rediscover the field from scratch. MCP and CLI access make Paperzilla output usable inside agent workflows, scripts, and recurring research briefs.

MCP server access

CLI access

Agent-ready paper streams

Structured research context

Recurring briefing workflows

Use cases

A focused feed for every research workflow

Use Paperzilla anywhere missing the right paper would slow down a project, weaken a decision, or leave an agent working from stale context.

Researchers

Track a narrow topic without checking every source, alert, and newsletter manually. See the papers most likely to matter before they disappear into the literature pile.

Labs and research teams

Keep projects, proposals, journal clubs, and student work aligned with the newest relevant literature.

R&D teams and founders

Monitor technical areas that could affect roadmap decisions, product direction, competitive analysis, or scientific claims.

AI research agents

Feed agents a continuously updated, topic-specific paper stream through MCP or CLI workflows, so they start from focused research context instead of the open paper firehose.

Example feeds

Example research feeds

Explore example feeds to see how Paperzilla tracks different research contexts, then use one as a starting point for your own topic. Browse the public digests for more.

Computer vision, machine learning, AI

Vision and multimodal models

Video grounding improves with lightweight VLM adapters

Long-context multimodal reasoning benchmarks

Evaluation traps in retrieval-augmented generation

Browse example feed

Medicine, immunology, public health

Long-Covid and immunology

T-cell signatures linked to symptom clusters

Post-viral dysautonomia review

Early antiviral trial results in high-risk cohorts

Browse example feed

NLP, language models, automation

Applied agents and tool use

Structured tool-use with safety rails

Latency-aware routing for production LLM systems

Recurring literature briefs from scoped sources

Browse example feed

Source-grounded

Grounded in papers, tuned for relevance

Paperzilla is designed to help you discover, verify, and act on relevant research without treating AI summaries as a replacement for the source paper.

Source links first

Every result points back to the original paper, so you can verify claims and read the source directly.

Relevance before volume

Paperzilla is built to reduce alert noise by ranking papers against the specific topic you care about.

Summaries as starting points

AI-generated summaries help with triage, but the paper remains the ground truth.

Feedback improves the feed

Your interactions and feedback help the feed become more focused over time.

FAQ

Frequently asked questions

Google Scholar alerts tell you when papers match a query. Paperzilla can accept forwarded alerts, combine them with monitored paper sources, and filter the results against your specific research topic so you get a focused feed instead of another noisy inbox.

Yes. You can forward Google Scholar-style alerts and other paper-alert emails to Paperzilla so they become inputs to your relevance-filtered feed.

Paperzilla currently harvests papers from sources such as arXiv, bioRxiv, medRxiv, ChemRxiv, and ChinaXiv. Additional source support can be added on request.

You define the research topic. Paperzilla compares incoming papers against that topic, ranks likely matches, and improves over time using feedback and recommender-style signals.

Paperzilla can deliver results through an in-app paper feed, daily or weekly email digests, RSS/Atom feeds, MCP server access, and CLI access.

Yes. Paperzilla is designed to provide relevance-filtered research context that AI agents and automation workflows can consume through MCP and CLI access.

Paperzilla is a continuous research monitoring system. It watches paper sources and alerts, filters incoming papers by relevance, and delivers a structured feed for humans, teams, and AI agents.

Paperzilla

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Built by agents + one human for research agents + their human.