Paper Lantern

Research intelligence for AI coding agents. Surfaces what 2M+ CS papers say at any technical decision your agent hits.

What it does

Your agent's training data freezes at a point in time. Paper Lantern gives it on-demand access to 2M+ CS research papers with evidence, tradeoffs, and implementation guidance. When your agent is about to pick a chunking strategy, a reranker, an eval method, or an agent memory pattern, it asks Paper Lantern what recent research says.

What it's used for

Prompting, evals, RAG (chunking / retrieval / reranking), agent memory, routing, fine-tuning, test generation, extraction, classification, code review, algorithm choice, architecture trade-offs. Any technical decision where recent CS research improves the outcome.

Tools

When it activates vs when it doesn't

• Activates: technique and architecture decisions where research evidence improves the outcome
• Skips: syntax questions, library API lookups, debugging, code formatting, general programming tasks

Install

npx paperlantern@latest

OAuths via device code, mints a pl_* API key, writes MCP config for Claude Code, Cursor, Windsurf, GitHub Copilot (VS Code), Codex, and Gemini CLI.

Manual server config

{
  "mcpServers": {
    "paper-lantern": {
      "type": "http",
      "url": "https://mcp.paperlantern.ai/chat/mcp?key=YOUR_KEY"
    }
  }
}

Links

• Website: paperlantern.ai/code
• Docs: paperlantern.ai/docs
• Official MCP Registry: ai.paperlantern/code
• Source: github.com/paperlantern-ai/paperlantern-cli

## Also published on

- Official MCP Registry: `ai.paperlantern/code` (published 2026-04-21)
- PulseMCP: auto-ingests from the official registry (appears within ~1 week)