Hey everyone, I’ve been experimenting with the Model Context Protocol (MCP), specifically trying to solve what I call the “Empty Prompt Problem”—the fact that our LLMs are completely blind to our physical state. If I’m experiencing context-switching fatigue or dopamine burnout after 9 hours of coding, standard AI tools will just keep feeding me high-density tokens, which only makes the brain fog worse. I wanted to build an agentic “circuit breaker” that forces me to stop. So, I built an open-source SDK and MCP Gateway to connect live biometric telemetry to local AI agents. Here is the architecture: The Telemetry (Android): I built a mobile app (Maha OS) that tracks metabolic baselines on the edge (Resting Heart Rate, HRV, Decision Velocity) to monitor cognitive load. The MCP Gateway (Node.js): An express server ( mcp-server.ts ) that holds an open Server-Sent Events (SSE) tunnel, broadcasting the user’s biological state as a secure ledger. The Agentic Steward (Python): A local agent ( maha_agent.py ) that monitors linguistic fatigue in my prompts and reads the MCP telemetry. The Intervention: If the agent detects Biological Instability (e.g., RHR spikes combined with erratic, short-burst prompting), it uses a registered MCP tool to autonomously trigger a hardware-level intervention. Right now, it pings the Android device to physically dim the screen, forcing a 5-minute parasympathetic reset. I’m trying to move AI away from just being a “productivity engine” and turn it into a sovereign biological steward that protects against algorithmic extraction. The gateway and the Python agent are open-sourced here: https://github.com/mayonerajan/maha-cognitive-gateway Would love feedback on the SSE implementation, or ideas on what other hardware-level circuit breakers developers would find useful when they hit terminal screen fatigue. submitted by /u/Magayone
Originally posted by u/Magayone on r/ArtificialInteligence