Hermes Agent

Hermes Agent is built around a learning loop. It creates skills from experience, improves them while using them, searches its own past conversations and builds a model of the person it works for across sessions.

It is not bound to a laptop. One gateway process serves Telegram, Discord, Slack, WhatsApp, Signal and the command line at once, with voice memo transcription and conversation continuity between them, so the agent can keep working on a cloud machine while you talk to it from a phone.

The project describes its own capabilities in five areas.

• Terminal interface: a full TUI with multiline editing, slash-command autocomplete, history, interrupt and redirect, and streaming tool output.
• Memory and recall: agent-curated memory with periodic nudges, full-text session search with summarization, and dialectic user modeling.
• Scheduled automations: a built-in cron scheduler runs daily reports, nightly backups or weekly audits unattended and delivers them to any platform.
• Delegation: isolated subagents handle parallel workstreams, and Python scripts call tools over RPC to collapse multi-step pipelines.
• Seven terminal backends: local, Docker, SSH, Singularity, Modal, Daytona and Vercel Sandbox, two of which hibernate when idle and wake on demand.

Any model works, whether through Nous Portal, OpenRouter, OpenAI or your own endpoint, and switching takes one command rather than a code change. Install scripts cover Linux, macOS, WSL2, Termux and native Windows, pulling in Python, Node.js and the other dependencies. It runs on a cheap VPS or a GPU cluster, suiting anyone who wants an agent that stays awake between sessions.