Hermes Agent
Nous Research's self-improving open-source agent: terminal UI plus messaging gateway, agent-curated memory and skills it writes and refines from experience.
Tags
Description
Works with any model provider (Nous Portal, OpenRouter, OpenAI, custom endpoints; switch with hermes model). Features from the README: full TUI, one gateway process for Telegram, Discord, Slack, WhatsApp and Signal, autonomous skill creation compatible with the agentskills.io standard, FTS5 session search, Honcho user modelling, a built-in cron scheduler, isolated subagents, and seven terminal backends (local, Docker, SSH, Singularity, Modal, Daytona, Vercel Sandbox). Also ships batch trajectory generation for training tool-calling models. Install: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash (native Windows via PowerShell).
Agent access
Related
- OpenClaw: Open-source personal AI assistant that runs on your own machine behind one Gateway and talks to you over WhatsApp, Telegram, Slack, Discord, iMessage and 20+ other channels.
- Honcho: Open-source memory infrastructure for stateful agents that models people, agents, groups and projects over time; managed or self-hosted.
- Agent Skills Specification: Open format for packaging agent capabilities as folders with a SKILL.md (YAML frontmatter + instructions) plus optional scripts and resources.
- Modal: Cloud platform for production AI: inference, training, sandboxes and serverless functions on one platform.
- Daytona: Secure and elastic infrastructure (sandboxes) for running AI-generated code.
- Vercel Sandbox: Ephemeral compute primitive that runs untrusted or agent-generated code in isolated Linux microVMs.
Guides & comparisons
- OpenClaw vs Hermes Agent vs Pi: open-source agents you run yourself (Comparison): Three fast-moving open-source agent runtimes compared: OpenClaw (gateway-first personal assistant), Hermes Agent (self-improving agent with memory, skills and cron) and Pi (minimal, extensible coding harness). Covers interfaces, models, memory, skills, MCP, automation, safety defaults and license.
Sources
Machine-readable
- JSON
- Markdown
- Source file on GitHub (edit via pull request)