Research discovery, refracted Beta

Find the right papers faster.

Hundreds of papers land every day. Knowra bends that flood into a handful worth your attention — and Scout tells you in seconds whether one deserves a deep read.

See Scout in action
  • On iPhone
  • In your AI assistant via MCP

How it works

Five seconds to decide.
Ten minutes a day to stay ahead.

Knowra fits the gaps in your day — a coffee line, a commute, the minute before a meeting.

  1. 01

    Discover

    A daily feed shaped by your fields. Swipe right to save, left to skip — every swipe sharpens what comes next.

  2. 02

    Scout

    Tap a card for a fast, structured read: the method signal, what to verify, the conditions it needs and where it breaks.

  3. 03

    Save

    Keep what matters, with arXiv IDs at hand. Search, filter by field, and export to RIS for Zotero when you're at your desk.

Scout

Between the abstract
and the PDF.

An abstract is too thin to judge. A full read is too expensive to waste. Scout sits in between — a mid-level screen that surfaces what actually matters for deciding whether a paper is worth your afternoon.

  • Method signal — what's genuinely new, in plain terms.
  • Worth verifying — the claims and experiments to look at first.
  • Conditions & limits — when it should work, and when it won't.

Grounded in the paper itself, with sections you can trace back.

Scout Reading paper…

Peridynamic Operators as Nonlocal Attention: A Physics View of Long Context

Method signal

Treats attention as a nonlocal integral operator with a learned horizon δ. Tokens interact only within δ, giving a physically motivated sparsity pattern rather than a hand-designed window.

Worth verifying

The perplexity gain at 128k tokens (Table 3) and whether the δ-ablation holds once compute is matched against sliding-window baselines.

Conditions

Assumes locally smooth token interactions; strongest on code and long-form prose.

Limitations

No results on retrieval-heavy tasks; custom kernel required for the reported speedups.

Illustrative brief Skip Save

Why it feels different

Built for discovery, not just search.

The paper that unlocks your project is rarely the one your feed already knows about. Knowra is designed to let it through.

01

One beam in. A whole spectrum out.

Five recall paths are blended and re-ranked into one feed — so you get depth in your field, and a little surprise from the next one over.

  • Vector

    Closest in meaning to what you save

  • Graph

    Linked through the research graph

  • Explore

    Methods from adjacent fields

  • Impact

    Work the field is paying attention to

  • Hot

    What's moving right now

02

Scout before the PDF

A middle screen that answers the real question: is this worth a deep read, and what should I check first?

03

Your swipes steer it

Save and skip are the only settings you need. Every signal re-ranks tomorrow's feed — no boolean queries, no alert fatigue.

04

Agent-ready library

The same index answers your AI assistant over MCP — free paper search, no API key required.

For AI assistants

Discover on your phone.
Keep researching in your AI assistant.

Add Knowra to Claude, Cursor, Codex or any MCP client. Your assistant searches the same library with the context of what you're stuck on right now — and brings back papers you can trace.

mcp.json
{
  "mcpServers": {
    "knowra": {
      "type": "http",
      "url": "https://mcp.knowra.app/mcp"
    }
  }
}
~/research — claude
Real results from the Knowra index · Oct 2026 search_papers

Let the flood pass.
Keep the light.

Set your fields once. Knowra handles the rest — every day.

Welcome back

We'll email you a one-time code — no password needed.

OR