Hermes Agent Complete Guide

Open-source, self-hosted AI Agent with long-term memory and Skills system

GitHub: NousResearch/hermes-agentOfficial: hermes-agent.nousresearch.comChinese Community: hermesagent.org.cn

📖 Introduction

Hermes Agent is an open-source AI Agent developed by Nous Research, designed for long-term task execution and continuous operation. Unlike IDE assistants, Hermes emphasizes:

• Cross-session Memory - Long-term memory of your projects, preferences, and work habits
• Reusable Skills - Turn solved problems into reusable skills
• Multi-platform Message Gateway - Stay online through Telegram, Discord, Lark, and more
• Self-hosted - Full control over data and runtime environment

✨ Core Features

1. Long-term Memory & Skills

Cross-session Memory

• Remembers project context, code structure, personal preferences
• Continuously learns your work habits
• Every conversation builds on historical context

Skills System

• Turn solved problems into reusable skills
• Compatible with agentskills.io open format
• Support team sharing and community contributions

2. MCP & Tool Integration

40+ Built-in Tools

• Terminal command execution
• File system operations
• Browser automation
• Image processing
• TTS (Text-to-Speech)
• Multi-model inference

MCP Support

• Compatible with Model Context Protocol
• Extensible custom tools
• Flexible toolset configuration

3. Multi-platform Message Gateway

Social Platforms

• Telegram
• Discord
• Slack
• WhatsApp
• Signal
• WeChat

Enterprise Platforms

• WeCom (Enterprise WeChat)
• Lark (Feishu)
• DingTalk

Use Case: Keep your Agent online across multiple platforms, receive tasks and push results anywhere, anytime.

4. Automation Scheduling

Built-in Cron

• Auto-generate daily reports
• Scheduled backups
• System health checks
• Timely reminders
• Information scraping

5. Model Compatibility

Chinese Models

• Qwen (Alibaba)
• GLM (Zhipu)
• Kimi (Moonshot)
• MiniMax

International Models

• Claude (Anthropic)
• Gemini (Google)
• Codex (OpenAI)

Other Interfaces

• OpenRouter and other proxies
• OpenAI-compatible APIs
• Local model support

🚀 Installation

System Requirements

• Linux / macOS / WSL2 / Windows
• Internet connection (for downloads and model calls)
• Optional: Docker environment

Quick Install

Linux / macOS / WSL2

curl -fsSL https://res1.hermesagent.org.cn/install.sh | bash

Windows PowerShell

irm https://res1.hermesagent.org.cn/install.ps1 | iex

Note: WSL2 is recommended for most Windows users as a long-term solution.

Configure Model

# Launch setup wizard
hermes setup

# Configure model
hermes model

Start Conversation

# Launch full TUI
hermes

Features include:

• Multi-line input
• Command completion
• Context compression
• Tool output streaming
• Session history

Connect Message Gateway

# Configure message gateway
hermes gateway setup

# Start gateway
hermes gateway

📚 Use Cases

Use Case 1: Terminal Task Execution

# Interact with Hermes directly in terminal
hermes

# Example: Analyze project code
> Help me analyze the code structure of this project and find potential optimization points

# Example: Generate daily report
> Generate a daily report based on today's git commits

Use Case 2: Multi-platform Continuous Work

Configure Telegram Bot

hermes gateway setup telegram

Usage Scenario

• Send tasks to Hermes via Telegram
• Hermes pushes results when done
• Interact with your Agent anywhere, anytime

Use Case 3: Automation Tasks

Create Scheduled Tasks

# Edit crontab
hermes cron edit

# Example: Generate daily report at 9 AM
0 9 * * * hermes task daily-report

# Example: System health check every hour
0 * * * * hermes task system-check

Use Case 4: Long-term Project Assistant

Project Initialization

# Create project config
hermes project init my-project

# Set project context
hermes project config --name "My Project" --tech "Python, React"

Continuous Collaboration

• Hermes remembers project structure and code standards
• Every conversation builds on project context
• Skills accumulate project-specific knowledge

🔧 Advanced Configuration

Environment Isolation

# Create isolated environments
hermes profile create work
hermes profile create personal

# Switch environment
hermes profile switch work

Command Approval

# Configure commands requiring approval
hermes config set approval.required "rm,git push,docker"

# Set approval timeout
hermes config set approval.timeout 300

Container Isolation

# Run tools in isolated containers
hermes config set sandbox.enabled true
hermes config set sandbox.image "hermes-sandbox:latest"

Vision Capabilities

# Enable vision understanding
hermes config set vision.enabled true

# Use vision features
> Analyze the UI issues in this screenshot [upload image]

🆚 Comparison with OpenClaw

Feature	Hermes Agent	OpenClaw
Token Usage	Lower (~30%)	Higher
Transparency	High, visible execution steps	Medium
Long-term Memory	Native support	Limited
Skills System	Built-in, agentskills.io compatible	Requires extra config
Message Gateway	Native multi-platform support	Requires extra integration
Migration	hermes claw migrate one-click	-
Model Support	Broad Chinese & international	Primarily Claude
Community	Active Chinese community	English community

Recommendations:

• Need long-term memory & Skills → Hermes Agent
• Need multi-platform message gateway → Hermes Agent
• Need lower token consumption → Hermes Agent
• Primarily use Claude → Either works

🛠️ Migrating from OpenClaw

# One-click migration
hermes claw migrate

# Migrates:
# - Configuration files
# - Conversation history
# - Custom settings

📊 Best Practices

1. Project Initialization Workflow

# 1. Create project directory
mkdir my-project && cd my-project

# 2. Initialize Hermes project
hermes project init

# 3. Configure project info
hermes project config --name "My Project" --description "Project description"

# 4. Set tech stack
hermes project config --tech "Python, FastAPI, PostgreSQL"

# 5. Start collaborating
hermes

2. Skills Development Workflow

# 1. Create skill
hermes skill create my-skill

# 2. Define skill functionality
# Edit ~/.hermes/skills/my-skill/skill.yaml

# 3. Test skill
hermes skill test my-skill

# 4. Publish skill (optional)
hermes skill publish my-skill

3. Team Collaboration Setup

# 1. Share project config
hermes project export > project-config.yaml

# 2. Team members import
git clone <project-repo>
cd project
hermes project import project-config.yaml

# 3. Share skills
hermes skill share --team

🔗 Related Resources

• GitHub: NousResearch/hermes-agent
• Official Docs: hermes-agent.nousresearch.com
• Chinese Community: hermesagent.org.cn
• Nous Research: nousresearch.com

🆘 FAQ

Q: What's the difference between Hermes Agent and IDE assistants?

A: Hermes emphasizes:

• Long-term context retention (cross-session memory)
• Reusable skills accumulation
• Multi-platform message gateway
• Self-hosting and data control

Q: Where should Chinese users start?

A:

1. Visit Chinese community hermesagent.org.cn
2. Check Chinese installation tutorial
3. Windows users should check Windows installation guide first
4. Join WeChat/Lark community groups

Q: What deployment methods are supported?

A:

• Local computer
• VPS server
• Docker container
• SSH remote environment
• Cloud dev environment (GitHub Codespaces, etc.)

Q: How to reduce token consumption?

A:

• Enable context compression
• Use appropriate models (Chinese models are cheaper)
• Accumulate skills to reduce repeated reasoning
• Configure command approval to avoid mistakes

📝 Summary

Hermes Agent is an open-source AI Agent for long-term tasks and continuous operation, especially suitable for:

• ✅ Projects requiring long-term memory and context retention
• ✅ Scenarios needing multi-platform message gateway
• ✅ Teams wanting to accumulate reusable skills
• ✅ Scenarios concerned about token consumption and cost
• ✅ Users requiring self-hosting and data control

Get Started:

curl -fsSL https://res1.hermesagent.org.cn/install.sh | bash
hermes setup
hermes

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License: MIT License · 2026 Nous Research