Hermes Agent

Hermes Agent is an open-source, self-improving AI agent from Nous Research, MIT licensed, tagged "The agent that grows with you." It is the only agent with a built-in learning loop: creating skills from experience, improving them in use, persisting knowledge, searching past conversations, and deepening its user model across sessions. The repository has drawn roughly 231K GitHub stars since July 2025.

Core Features

• Closed learning loop: Agent-curated memory, autonomous skill creation after complex tasks, self-improving skills, FTS5 session search with LLM summarization, Honcho dialectic user modeling, and agentskills.io standard compatibility.
• Multi-channel gateway: Telegram, Discord, Slack, WhatsApp, Signal, and CLI via one gateway, with voice memo transcription and cross-platform continuity.
• Scheduled automations: Built-in cron scheduler delivers results to any platform.
• Delegation: Spawns isolated subagents in parallel; Python scripts call tools via RPC.
• Seven terminal backends: Local, Docker, SSH, Singularity, Modal, Daytona, Vercel Sandbox; Daytona and Modal hibernate when idle.
• Model freedom: Nous Portal, OpenRouter, OpenAI, or your own endpoints; switch with hermes model, no lock-in.

Use Cases

• Personal agent: Runs on a $5 VPS, GPU cluster, or serverless infra; talk via Telegram while it works on a cloud VM.
• Automation hub: Cron jobs deliver reports and recurring research to any chat platform.
• Research: Generate and compress trajectories as training data.
• Serverless: Hibernating Daytona and Modal backends keep an always-on agent cheap.

Pricing

Free and open source under MIT. You pay only for infrastructure (a $5 VPS works) and your model provider.

Advantages

1. vs nanobot: Both are self-hosted multi-channel agents, but only Hermes Agent has a closed learning loop that creates and improves skills and models the user.
2. vs OpenAI Agents SDK: The SDK is a library; Hermes Agent is a finished agent with channels, cron, TUI, memory, and seven backends, model-agnostic rather than OpenAI-first.
3. vs CrewAI: CrewAI orchestrates role-based agent teams; Hermes Agent is one persistent agent that learns you and lives in your chat apps.

Getting Started

1. Install: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
2. Pick a model: Connect Nous Portal, OpenRouter, OpenAI, or your own endpoint.
3. Talk: Use the terminal TUI, or connect Telegram, Discord, Slack, WhatsApp, or Signal.
4. Docs: Documentation and the Hermes Desktop app live at hermes-agent.nousresearch.com.

FAQ

Is Hermes Agent free?

Yes, MIT-licensed open source; you only cover infrastructure and model API costs.

Does it require Nous models?

No. It is model-agnostic across Nous Portal, OpenRouter, OpenAI, and custom endpoints.

Where does my data live?

On your own machine or server; memory, session search, and skills are all self-hosted.

Alternatives

• nanobot: Lightweight Python personal agent with WebUI and MCP.
• CrewAI: Role-based multi-agent orchestration.
• OpenAI Agents SDK: Library for building agents on OpenAI primitives.

Tips

1. Give it real work: Skill creation triggers after complex tasks, so real projects grow its skill library fastest.
2. Use serverless backends: Modal and Daytona hibernate when idle, cutting always-on costs.
3. Review created skills: Skills self-improve, but occasional review keeps behavior aligned; scope terminal access carefully.

Conclusion

Hermes Agent turns a static chatbot into a partner that compounds: every task becomes a skill, every correction becomes memory, every session deepens its model of you. For an open, model-agnostic agent that grows with you, install it and start the loop.