The full upstream README, mirrored here for reference. Install config, tool schemas, adoption signals, and an original overview live on the Paper Lantern listing page.
Research intelligence that makes your AI coding agent smarter - one command setup.
Paper Lantern gives your AI coding agent access to 2M+ CS research papers - the right technique for your problem, with tradeoffs, benchmarks, and implementation guidance.
That's it. Pick your agents, log in, and Paper Lantern is configured.
Prefer to set up manually, or using a client not listed above? See paperlantern.ai/docs for per-agent config snippets and the raw MCP endpoint.
The setup CLI:
Once configured, your agent gets these tools:
| Tool | What it does |
|---|---|
explore_approaches | Survey 4-6 approach families with evidence and tradeoffs |
deep_dive | Investigate one technique in depth - implementation, hyperparameters, failure modes |
compare_approaches | Side-by-side comparison of 2-3 candidates |
check_feasibility | GO / PROTOTYPE / RECONSIDER verdict given your constraints |
give_feedback | Tell us what helped and what didn't |
Paper Lantern activates when your agent is making technical decisions where research evidence could improve the outcome - choosing between algorithms, architectures, or techniques.
It does not activate for syntax questions, library lookups, debugging, or general programming tasks.