I wanted an always-on AI agent for email, calendar, and scheduled tasks - but I didn't want to run a codebase I couldn't fully understand. So I built one small enough to read in a sitting.
I was inspired by Karpathy's post about NanoClaw, and how a smaller source code footprint leads to better security and extensibility. But even NanoClaw was harder to understand than I expected - a lot of logic for supporting multiple channels simultaneously, and it felt sluggish due to container startup time on every message. So I built an even smaller agent that keeps a single session on an always-on Docker container. It's about 4x smaller in codebase size and noticeably faster.
The architecture is deliberately boring: a single Node.js process manages a Docker container running the Claude agent SDK. Host and container communicate through atomic JSON files. No databases, no message queues.
Since the entire codebase fits in Claude's context window, the agent can modify its own source to add new capabilities — Gmail, Google Calendar, or whatever MCP server you point it at. Every source file is listed in the README with line counts, I encourage you to read it!
Would love your feedback on my approach and welcome any contributions :)
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