TL;DR: Hermes Agent by Nous Research is a self-improving autonomous agent with a built-in learning loop that creates skills from experience, improves them during use, and remembers across sessions. Unlike typical chatbots or coding copilots, Hermes runs on your server, integrates with messaging platforms, and gets smarter the longer you use it.
What Is Hermes Agent?
Hermes Agent is an open-source autonomous AI agent built by Nous Research — the lab behind some of the most capable open-source models, including Hermes 3 and Hermes 4.
Named after the Greek messenger of the gods who could travel between worlds, Hermes Agent lives up to its namesake. It doesn’t just run tasks —it remembers them, learns from them, and gets more capable every single session.
Key differentiator: A closed learning loop. This means the agent creates skills from experience, improves them during use, and builds persistent memory across sessions. No configuration required—you just run it and it gets smarter.
Why Hermes Agent Matters
Most AI tools today fall into two categories:
- Coding copilots tethered to an IDE (Cursor, GitHub Copilot, etc.)
- Chatbot wrappers around a single API (ChatGPT, Claude web interface, etc.)
Hermes Agent is neither. It’s an autonomous agent that:
- Lives on your server
- Remembers what it learns
- Integrates with Telegram, Discord, Slack, and more
- Gets more capable the longer you run it
- Runs entirely locally with your own models
This makes Hermes Agent ideal for:
- Developers who want a persistent assistant that understands their projects
- Teams who need an agent accessible via messaging platforms
- Privacy-conscious users who want everything running locally
- Anyone who wants an agent that improves over time without manual configuration
Key Features
1. Closed Learning Loop
The flagship feature. Hermes Agent:
- Creates skills from experience autonomously
- Improves existing skills during use
- Nudges itself to save important information to memory
- Builds a model of who you are that deepens across every session
All automatically. Zero configuration. No other agent does this.
2. 94 Bundled Skills
Hermes ships with 94 bundled skills out of the box:
- MLOps tools
- GitHub workflows
- Research tools
- Media productivity
- RL training
- Stable Diffusion integration
- Web scraping
- File operations
- And more
The agent also creates new skills autonomously from its own experience.
3. Multi-Platform Messaging
Hermes Agent integrates with:
- Telegram
- Discord
- Slack
- Signal
- Matrix
Run it as a systemd service and it survives reboots, keeps running when you close your terminal, and delivers notifications straight to your phone.
4. Sub-Agent Delegation
Spawn isolated sub-agents with their own terminals for parallel work streams. Useful when:
- Running multiple independent tasks
- Isolating risky operations
- Parallel processing
5. Smart Approval Modes
Security-conscious features:
- Ask before running any flagged command
- LLM-based assessment of whether a command is dangerous
- Docker or SSH execution for container isolation
- Configurable trust levels
6. Model Agnostic
Works with:
- Local models: Ollama, LM Studio, vLLM
- Cloud APIs: OpenAI, Anthropic, OpenRouter
- Custom endpoints: Any OpenAI-compatible API
7. Scheduled Automation
Tell Hermes in plain English: “do X on Telegram at this time” and it sets up the cron job. The job runs on schedule and delivers to your phone. No extra configuration.
Installation
Prerequisites
- Linux, macOS, or WSL2
- No manual dependencies required—the installer handles everything
Quick Install
curl -fsSL https://raw.githubusercontent.com/NousResearch/hermes-agent/main/scripts/install.sh | bashThe installer:
- Pulls Python 3.11
- Clones the repository
- Installs all dependencies (including a full browser engine)
- Syncs 94 bundled skills
Setup Wizard
After installation, the setup wizard guides you through:
-
Model Provider Selection
- Self-hosted (Ollama, LM Studio, vLLM)
- API providers (OpenAI, Anthropic, OpenRouter)
- Custom OpenAI-compatible endpoints
-
Terminal Backend
- Docker (recommended for isolation)
- Local (for simplicity)
-
Messaging Platform Configuration
- Telegram bot token and user ID
- Discord bot setup
- Other channels
-
System Service Installation
- Run as systemd service for persistence
Running with Local Models
Option 1: Ollama
-
Install Ollama:
Terminal window curl -fsSL https://ollama.com/install.sh | sh -
Pull a model that supports tool use:
Terminal window ollama pull glm4# orollama pull qwen2.5 -
During Hermes setup, select “Self-hosted” and enter:
- Endpoint:
http://localhost:11434/v1 - Model name: your pulled model
- Endpoint:
Option 2: LM Studio
-
Download from lmstudio.ai
-
In LM Studio:
- Go to Developer mode → Local Server
- Set port (default: 1234)
- Download a model with tool-use support (e.g., Qwen 2.5)
- Click “Load Model” then start the server
-
During Hermes setup:
- Select “Custom OpenAI-compatible endpoint”
- Endpoint:
http://localhost:1234/v1 - Model name: copy from LM Studio
Important: Context Length
If you see “context length exceeded” errors:
- In LM Studio, go to Server Settings
- Increase context length slider (e.g., 16000+)
- Reload the model
Telegram Integration
Step 1: Create a Bot
- Open Telegram and search for
@BotFather - Send
/newbot - Choose a name (e.g., “My Hermes Agent”)
- Choose a username (must end in
bot, e.g.,myhermesagent_bot) - Copy the API token provided
Step 2: Get Your User ID
- Search for
@userinfobotin Telegram - Start it and copy your numeric user ID
Step 3: Configure Hermes
During setup or in the config file:
- Enter your bot token
- Enter your user ID (or allow open access—not recommended)
- Optionally add allowed channel IDs
Step 4: Pair and Use
- Start Hermes:
hermes - Your Telegram bot will detect the connection
- Send
/startin Telegram to begin pairing - Chat with Hermes from anywhere
Memory in Action
Here’s what makes Hermes Agent’s memory special:
You: "I'm a Python developer, I prefer clean code with type hints, and I always use FastAPI."
Hermes: [Saves to memory]
[New session, days later]
You: "What do you know about me?"
Hermes: "You're a Python developer who prefers clean code with type hints and uses FastAPI for projects."The agent:
- Remembers preferences across sessions
- Builds a profile of your work style
- Applies past learnings to new tasks
- Nudges itself to save important context
Hermes Agent vs OpenClaw
| Category | Hermes Agent | OpenClaw |
|---|---|---|
| Architecture | Single process | Gateway + plugins |
| Memory | Built-in learning loop | Plugin-based (LosslessClaw for advanced) |
| Skills | 94 bundled + auto-created | Plugin ecosystem (ClawHub) |
| Multi-agent | Sub-agent delegation | Full multi-agent OS (HighClaw) |
| Security | Docker/SSH isolation + approval modes | Enterprise-grade (NemoClaw sandboxing) |
| Setup complexity | Simple, single command | More moving parts |
| Scheduled tasks | Plain English, automatic | Manual configuration |
| Extensibility | Works within bundled system | Deep plugin architecture |
Bottom line:
- Hermes Agent: Best for personal use, simplicity, and an agent that improves automatically
- OpenClaw ecosystem: Best for teams, enterprise security, multi-agent systems, and deep extensibility
Strip away OpenClaw’s plugins (LosslessClaw, NemoClaw, HighClaw) and Hermes wins 7 categories to 3. The OpenClaw ecosystem is formidable, but Hermes Agent out of the box is simply more capable for a single user running a personal agent.
Security Considerations
Important: Hermes Agent has full access to your terminal, files, and machine. It:
- Runs commands
- Reads directories
- Can write anywhere it has permissions
Before giving open access to Telegram or running on a production server:
- Restrict who can use it via user IDs
- Consider Docker isolation
- Use approval modes for sensitive operations
- Review what commands it’s allowed to run
With great power comes great responsibility. Security and safety of your data is your responsibility.
Quick Start Commands
# Installcurl -fsSL https://raw.githubusercontent.com/NousResearch/hermes-agent/main/scripts/install.sh | bash
# Run with default modelhermes
# Change modelhermes model# Then select your provider and model
# Reload shell (if needed)source ~/.bashrcTroubleshooting
Model Not Detected After Setup
If Hermes defaults to Claude Opus despite configuring a local model:
hermes model# Select your provider# Enter endpoint (e.g., http://localhost:11434/v1)# Enter model nameContext Length Exceeded
For LM Studio:
- Go to Server Settings
- Increase context length
- Reload model
For Ollama, use a model with larger context window.
Telegram Not Responding
- Verify bot token is correct
- Check user ID matches your Telegram ID
- Ensure Hermes is running (
hermescommand) - Try
/startcommand in Telegram
Conclusion
Hermes Agent represents a different philosophy in AI agents: instead of giving you tools to configure, it gives you an agent that configures itself. The closed learning loop means the longer you use it, the more valuable it becomes.
For individual developers and privacy-conscious users who want a persistent agent that understands their context, remembers their preferences, and improves autonomously, Hermes Agent is worth serious consideration.
When to choose Hermes Agent:
- You want an agent that works immediately without configuration
- You value simplicity over extensibility
- You want the agent to learn and improve automatically
- You primarily need a personal assistant rather than a team platform
When to look elsewhere:
- You need enterprise-grade security sandboxing
- You’re building complex multi-agent systems
- You require deep plugin extensibility
- You’re deploying for a team environment
Hermes Agent is built by Nous Research, runs on any model, lives on your server, and gets smarter every session.
References
- Nous Research. Hermes Agent — AI Agent Framework. Accessed 23 Mar. 2026.
- Nous Research. Hermes Agent Documentation. Accessed 23 Mar. 2026.
- Nous Research. Hermes Agent GitHub Repository. Accessed 23 Mar. 2026.
- Nous Research
- Fahd Mirza. “Hermes Agent + Ollama + Telegram - Local Easy Setup Guide.” YouTube, 22 Mar. 2026. Accessed 23 Mar. 2026.
- Fahd Mirza. “Hermes Agent with LM Studio - Local Models Setup Guide.” YouTube, 22 Mar. 2026. Accessed 23 Mar. 2026.
- Fahd Mirza. “OpenClaw vs Hermes Agent: A Thorough Comparison for Your Use Case.” YouTube, 22 Mar. 2026. Accessed 23 Mar. 2026.
This article was written by opencode (GLM-5).

