DOOM MCP vs Libretto

Chris Nager built a fully playable DOOM that runs as an MCP (Model Context Protocol) app, rendering inline inside Claude and ChatGPT without a separate browser tab. The architecture uses two MCP tools — create_doom_session for inline-capable hosts and get_doom_launch_url as a browser fallback — combined with cloudflare/doom-wasm for the game runtime and a signed token system that maintains session state across both surfaces. The result is the same session whether you're playing inline or in a tab. The key technical challenge was avoiding iframe and CSP (Content Security Policy) issues. Rather than embedding a browser page inside the MCP iframe, the DOOM canvas runs directly inside the host's iframe — a subtle but critical distinction that resolved a class of rendering and input-handling bugs. The final implementation is intentionally stripped down: no save/load, no persistence adapters, just stable playable DOOM. Beyond the novelty, this project is a concrete demonstration that MCP apps are interactive surfaces, not just tool-calling JSON endpoints. The progressive enhancement pattern — same signed-token foundation serving both inline and browser modes — is a reusable architecture for any game or interactive experience that wants to live inside an AI assistant. Nager open-sourced the implementation and the blog post is a detailed technical breakdown.

Libretto is an open-source TypeScript toolkit for building and maintaining browser automations that are actually reliable. Unlike most AI-driven browser tools that use probabilistic reasoning to select elements at runtime, Libretto works by having the AI generate deterministic selectors and action sequences upfront — then executing them with zero LLM involvement at runtime. The AI is your authoring tool, not your runtime dependency. The core insight: most AI browser automations fail in production because they call an LLM on every page interaction. Libretto flips this by using AI to write and update the automation scripts, but running them as ordinary code. When a site changes and your automation breaks, Libretto detects the failure and prompts you to let AI update the selector — then it's deterministic again. Built by the team at Saffron Health, the library hit HN's front page today and is generating discussion as a more pragmatic alternative to fully autonomous browser agents. For anyone who's tried Playwright with AI wrappers and found them unreliable in CI/CD, this is the architecture that's been missing.