Paper Lantern is an MCP server that gives AI coding and chat agents access to over 2 million computer science research papers, distilling them into the right method for your problem — tradeoffs, benchmarks, and how to implement it — delivered directly into Claude Code, Cursor, Windsurf, GitHub Copilot, Cline, Codex, Gemini CLI, Claude.ai, or ChatGPT. For each query it reasons over hundreds of papers, finds multiple candidates for your problem, evaluates their limitations and applicability to your specific setting, and returns implementation-ready guidance such as hyperparameters, failure modes, and what to watch out for. It covers retrieval and RAG, prompt engineering, few-shot and in-context learning, LLM-as-judge and evaluation, output control, recommendation systems, knowledge graphs, vector indexes, plus systems design, networking, databases, security, NLP, and computer vision. Automatic setup detects your editor, authenticates, and writes the config via a single `npx paperlantern@latest` command (Node.js 18+); manual setup uses an API key starting with pl_. It was built by an ex-AWS Bedrock LLM/RAG lead and validated with 9 published benchmarks and an autoresearch case study showing measurable quality gains. Paper Lantern is ideal for engineers and researchers who want their coding agent to ground decisions in peer-reviewed research instead of its training data, closing the gap between what researchers know and what your agent has seen, with 300+ engineers and researchers already using it.
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