NousResearch's Hermes Agent has crossed 13,600 GitHub stars, driven by rapid community adoption following the v0.4.0 release on March 23. The open-source agent distinguishes itself with a built-in learning loop: after completing complex tasks, it writes structured "Skill Documents" — searchable markdown files that grow over time, so the agent gets faster and more capable the longer it runs.

What's New in v0.4.0

The headline feature is an OpenAI-compatible API server, which exposes Hermes as a /v1/chat/completions endpoint. This means any tool that targets the OpenAI API — editors, scripts, apps — can point at a local Hermes instance instead. Six new messaging adapters were also added: Signal, DingTalk, SMS (via Twilio), Mattermost, Matrix, and Webhook, joining the existing Telegram, Discord, and WhatsApp support.

Other additions include Claude Code-style @file and @url context injection, four new inference providers (GitHub Copilot, Alibaba Cloud/DashScope, Kilo Code, and OpenCode), MCP server management with OAuth 2.1, and over 200 bug fixes.

How It Works

Hermes uses FTS5 full-text search and LLM summarization for cross-session recall, and integrates with Honcho for user modeling. It runs on a standard VPS, a GPU cluster, or serverless infrastructure that hibernates when idle. A one-command migration path exists for OpenClaw users.

The project is MIT-licensed, works on Linux, macOS, and WSL2, and supports any model endpoint through OpenRouter, Nous Portal, or custom servers.

With v0.3.0 in mid-March already delivering a scheduled automation layer and parallel subagents, NousResearch has been shipping a new major version roughly weekly.