
Get a quick overview of the Hermes agent course, including installation options and architecture. Learn how Hermes uses skills, context management, and memory to guide practical workflows.
Install Hermes Agent across local, sandbox environments, separate devices, and vps setups, then configure llms and telegram, and run Hermes locally or on a vps.
Explore four practical installation options for Hermes Agent—local, sandboxed, separate device, and a VPS—highlighting their advantages, risks, and best-use scenarios for secure, persistent automation.
Install and run the Hermes agent on a VPS using a docker container, with one-click hosting options and clear onboarding steps.
Install Hermes agent on a suitable device, choose a provider and models, onboard with skills and tools, connect to Telegram (or Slack), and explore the dashboard.
Learn the basics of Hermes Agent, including built-in tools, onboarding and memory files, and VPS setup with SSH and VS Code to optimize context and automation.
Onboard your Hermes agent by creating a personalized user.md profile, capture interests, career, goals, and personal details, and enable memory updates as the agent learns over messages.
Learn to access and manage your VPS files from VS Code using Remote SSH extension, connect as root, and explore the Hermes agent and memory, dotenv, and docker compose files.
Manage the Hermes agent's context by compressing tokens and saving conversations to avoid waste. Use slash commands to start new sessions, clear history, and review usage.
Learn how Hermes agent uses the model context protocol with a Supabase MCP server to connect to a database, create tables, insert data, and update records.
Use the command line interface as the native way for an ai agent to call tools, preferring CLIs over MCB servers and skills, with GitHub CLI as a concrete example.
Learn to create, automate, and self-improve Hermes agent skills, integrate with cron jobs, and connect via MCP, plugins, and CLIs for extensible automation.
Explore Hermes Agent use cases from fitness and nutrition to course editing, Zapier MCB automation, smart home control, coding with sub-agents, Obsidian wiki, and local models.
Harness an MCP server to manage mails and calendar, and over 8000 apps with Hermes agent, wiring Gmail, Google Sheets, and Zapier through cloud code workflow.
Learn how Hermes agent connects to home assistant to control cameras, climate, lights, doors, and other smart home domains, with pre-built skills and plugins.
Explore sub-agent delegation and the Kanban multi-agent board to run parallel tasks, manage persistent profiles, and automate triage with cron jobs in Hermes.
Discover how Hermes serves as a personal trainer, video editor, and automation agent—planning meals, editing footage, and coordinating apps for practical, automated workflows.
Build your own Hermes agent by applying the course’s recap of LLM harness, tools, memory and self-improving workflows, and learn installation, onboarding, and practical automation for a personal assistant.
Hermes Agent: Build a Self-Improving Open-Source AI Agent
Hermes is an open-source AI agent that grows with you.
Similar in spirit to OpenClaw, it can run on your computer or server, use tools, execute commands, automate workflows, manage memory, connect to external apps, and work with systems like Telegram, MCP, Ollama, Supabase, GitHub, Claude Code, Codex, ComfyUI, Obsidian, and more.
In this course, you will learn how to install Hermes, configure it, extend it with skills, connect it to tools, automate real workflows, and build self-improving agent systems that can support you in research, coding, productivity, content creation, and personal automation.
This is not a course about simple prompting tricks.
It is a practical, project-based course for people who want to understand how modern AI agents actually work — including tools, skills, memory, permissions, plugins, hooks, MCP servers, local models, subagents, scheduled tasks, and security.
What You Will Build and Learn
The course starts from zero.
First, you will learn what Hermes Agent is, how the harness works, how the architecture is structured, and why Hermes is different from a normal chatbot.
Then you will install Hermes in different ways:
locally on Mac, Linux, or Windows with WSL2
on a VPS server
inside a Docker container
on a separate device or sandbox environment
You will configure LLMs, connect Telegram, use the Hermes dashboard, switch models, run basic commands, and understand how to work with Hermes in a real setup.
Hermes Agent Foundations
You will learn the core concepts behind Hermes Agent:
installation options and setup workflows
VPS setup with Docker
Windows setup with WSL2 Ubuntu
local installation on Mac, Linux, and Windows
basic Hermes commands
model switching
dashboard usage
documentation structure
the Hermes harness and agent architecture
By the end of this part, you will have Hermes running and understand how the system is built.
Practical Hermes Workflows
After the setup, you will move into real usage.
You will test Hermes with browser automation, manage files on a VPS with VS Code and SSH, onboard your agent, work with the user file, manage memory, customize personality with soul file, and use context management to save tokens.
You will also learn:
how Hermes uses tools
how skills work
how to manage permissions
how slash commands work
how to run scheduled tasks with cron jobs
how to enable voice input and output
how to use Hermes as a more personal AI assistant
This turns Hermes from a terminal-based AI tool into a practical agent you can actually use.
Advanced Hermes Agent Systems
The course then moves into more advanced agent workflows.
You will learn how to create your own Hermes skills, build self-improving skills, automate ComfyUI workflows, connect MCP servers, work with Supabase and SQL, bundle tools with plugins, use hooks for automation and logging, and integrate command-line tools like the GitHub CLI.
You will also explore reinforcement learning workflows, LoRA creation, and more advanced ways to extend Hermes beyond the default setup.
Topics include:
custom Hermes skills
self-improving skills
ComfyUI automation
MCP server integration
Supabase and SQL
plugins
hooks
CLI integrations
GitHub CLI
reinforcement learning
LoRA creation
Hermes Pro Workflows and Real Use Cases
In the pro section, you will see how Hermes can be used in more complex workflows.
You will explore use cases for fitness and nutrition, email and calendar management, smart home control, video editing, coding, repo monitoring, subagents, multi-agent delegation, Kanban boards, Obsidian, RAG-style knowledge systems, local models with Ollama, and automation through Zapier MCP.
You will learn how Hermes can connect to larger AI systems and work together with tools like Claude Code, Codex, Claude Design, Obsidian, Ollama, and MCP servers.
Use cases include:
Hermes as a personal assistant
Hermes for video editing workflows
Hermes for email and calendar automation
Hermes with Zapier MCP and thousands of apps
Hermes as a smart home assistant
Hermes for coding and repo monitoring
Hermes with Claude Code, Codex, and Claude Design
subagents and multi-agent delegation
Kanban-based task management
Obsidian and LLM wiki workflows
RAG-style knowledge databases
local models with Ollama
AI Agent Security
Powerful AI agents are useful, but they also introduce new risks.
That is why the final section covers important security topics for AI agents, including jailbreaks, prompt injections, tool poisoning, MCP rug pulls, hidden instructions, unsafe permissions, and the risks of giving agents access to files, APIs, terminals, tools, and external systems.
You will learn what can go wrong, what to watch out for, and how to think more carefully when building and using agentic systems.
By the End of This Course
By the end of the course, you will understand how to install Hermes Agent, configure it, connect it to tools, customize its memory and personality, build your own skills, automate tasks, work with MCP servers, use plugins and hooks, run scheduled jobs, connect external apps, use local models, delegate work to subagents, and think more clearly about AI agent security.
Hermes Agent should no longer feel like a mysterious open-source project.
It should feel like a practical AI agent system you can run, control, extend, and use for real work.
If you want to stop using AI only as a chatbot and start building your own open-source AI agent workflows with Hermes Agent, this course gives you the practical roadmap.