About Paper Lantern
Paper Lantern is an MCP server published by paperlantern-ai in the Search category: research intelligence for AI coding agents. 2M+ CS papers with evidence and tradeoffs.
Six months or more without a commit doesn't mean the server is broken, but check the open issues before depending on it in production.
Install
git clone https://github.com/paperlantern-ai/paperlantern-cliThis server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.
Tools (5)
check_feasibilityGO / PROTOTYPE / RECONSIDER verdict given your constraints
Parameters not published.
compare_approachesSide-by-side comparison of 2-3 candidates
Parameters not published.
deep_diveInvestigate one technique in depth - implementation, hyperparameters, failure modes
Parameters not published.
explore_approachesSurvey 4-6 approach families with evidence and tradeoffs
Parameters not published.
give_feedbackTell us what helped and what didn't
Parameters not published.
Ask AI
Ask AI about Paper Lantern
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README
paperlantern
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.
Quick start
npx paperlantern@latest
That's it. Pick your agents, log in, and Paper Lantern is configured.
Supported agents
- Claude Code
- Cursor
- Windsurf
- GitHub Copilot (VS Code)
- Codex
- Gemini CLI
- Cline
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.
What it does
The setup CLI:
- Authenticates via OAuth (opens browser)
- Configures the MCP server for your selected agents
- Installs agent rules so your agent knows when to use Paper Lantern
Tools available
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 |
When your agent uses Paper Lantern
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.
Links
README copy captured when this server was indexed; it may lag the repository. The original is authoritative.