Paper Lantern

Name: Paper Lantern
Author: paperlantern-ai

Research intelligence for AI coding agents. 2M+ CS papers with evidence and tradeoffs.

paperlantern-ai0 stars0 forksAI & Agents

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Install

mcp_config.json

{
  "mcpServers": {
    "ai-paperlantern-code": {
      "url": "https://mcp.paperlantern.ai/chat/mcp",
      "type": "streamable-http"
    }
  }
}

Documentation

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

Sourced from the repository README.

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