DOOM MCP vs Embedist

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.

Embedist is an open-source Windows desktop IDE for embedded firmware development that puts AI directly in your workflow. Built with Tauri 2 and React, it combines board-aware AI debugging (with hardware context for ESP32 and Arduino), real-time serial monitoring, PlatformIO build integration, and a Monaco editor into a single 5.7 MB app. Supports six AI providers including OpenAI, Anthropic, Google, DeepSeek, Ollama, and NVIDIA NIM — so you can keep it fully local or cloud-connected.