Server data from the Official MCP Registry
Research intelligence for AI coding agents. 2M+ CS papers with evidence and tradeoffs.
About
Research intelligence for AI coding agents. 2M+ CS papers with evidence and tradeoffs.
Remote endpoints: streamable-http: https://mcp.paperlantern.ai/chat/mcp
Security Report
Valid MCP server (1 strong, 1 medium validity signals). 1 known CVE in dependencies Imported from the Official MCP Registry.
Endpoint verified · Requires authentication · 2 issues found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
Permissions Required
This plugin requests these system permissions. Most are normal for its category.
How to Connect
Remote Plugin
No local installation needed. Your AI client connects to the remote endpoint directly.
Add this to your MCP configuration to connect:
{
"mcpServers": {
"ai-paperlantern-code": {
"url": "https://mcp.paperlantern.ai/chat/mcp"
}
}
}Documentation
View on GitHubFrom the project's GitHub 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.
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