Overview

Hermes Agent: What It Is and How to Run It

Hermes Agent is a self-improving AI agent built by Nous Research. It runs as a long-lived assistant rather than a chat window: it keeps memory between sessions, loads skills, calls tools, and answers on the messaging platforms your team already uses. This page is the starting point. It covers what the agent actually is, which parts you have to run yourself, and which deployment path fits the work in front of you.

Updated Sep 16, 202610 min read

Deployment route

01
Decide where the agent runs
The desktop installer, your own server, and managed hosting all run the same agent. The choice is about who carries the maintenance burden, not about which features exist.
02
Choose a model provider
Connect a provider key for Anthropic, OpenAI, Google, or OpenRouter, or point the agent at a local model. Provider routing and fallbacks can be layered on after the first reply works.
03
Connect one messaging channel
Pick the single channel your team already monitors, such as Telegram, Discord, Slack, or WhatsApp. One working channel teaches you more than five half-configured ones.
04
Prove one end-to-end reply
Send a real message in the target channel and confirm the answer. A healthy runtime is not evidence that permissions and credentials are wired correctly.
05
Add the next layer
Only after the first reply works: connect MCP tool servers, add scheduled runs, enable voice, or bring a second channel online.

Four-step path

How do you get from zero to a working Hermes Agent?

Four decisions take you from reading about the agent to a running assistant that answers in a real channel.

Step 01
Decide where the agent runs
The desktop installer, your own server, and managed hosting all run the same agent. The choice is about who carries the maintenance burden, not about which features exist.
Step 02
Choose a model provider
Connect a provider key for Anthropic, OpenAI, Google, or OpenRouter, or point the agent at a local model. Provider routing and fallbacks can be layered on after the first reply works.
Step 03
Connect one messaging channel
Pick the single channel your team already monitors, such as Telegram, Discord, Slack, or WhatsApp. One working channel teaches you more than five half-configured ones.
Step 04
Prove one end-to-end reply
Send a real message in the target channel and confirm the answer. A healthy runtime is not evidence that permissions and credentials are wired correctly.
Step 05
Add the next layer
Only after the first reply works: connect MCP tool servers, add scheduled runs, enable voice, or bring a second channel online.

What is Hermes Agent?

Hermes Agent is a self-improving AI agent from Nous Research that runs as an always-on assistant with persistent memory, reusable skills, and tool access across messaging platforms.

The important difference from a chat product is persistence. You configure it once and it stays available, with the same memory and the same tool access, in whichever channel you connected.

It keeps memory between sessions instead of forgetting each conversation.
It loads skills, so a repeated workflow becomes a reusable capability.
It calls tools, including MCP servers, web search, browsers, and a sandboxed terminal.
It runs as a gateway bot on more than twenty messaging platforms.
It is open source, so nothing about the runtime is a black box.

What is Hermes Agent not?

It is not a chat website, not a coding-only assistant, and not a service you can only reach through somebody else's interface.

It is not a stateless chatbot that starts from zero on every message.
It is not limited to code editing; the same runtime handles research, ops, and support work.
It is not locked to one provider, so a model outage is a configuration change rather than a migration.

What do you actually have to run?

The runtime itself needs a host, a provider key, and one channel integration. Everything else, from memory to skills to tool servers, is configuration on top of that runtime.

A host that stays online, which is a laptop for evaluation and a server or managed deployment for real use.
A model provider key, or a local model if data cannot leave your network.
One messaging channel with credentials you control, such as a Telegram bot token.
A configuration file that stores provider settings, channel settings, and integrations.

Which deployment option should you pick?

Evaluate on the desktop installer, then choose self-hosted or managed hosting based on whether you want to own uptime and upgrades or hand them off.

Desktop installer: fastest way to see the agent work, and it suits a single person on one machine.
Self-hosted: full control over data location, networking, and versions, at the cost of operating a server.
Managed hosting: a running assistant without provisioning a VPS, maintaining containers, or chasing restarts.

Where should you go next?

Start with the quickstart if you want the shortest path to a working reply, then move to the guide or use case that matches the job you are automating.

Which primary sources support this page?

Product behavior is checked against the current deployment flow. These external links provide the upstream project or channel documentation used for setup details.

Direct answers

Frequently asked questions

Is Hermes Agent free?

The agent itself is open source and licensed by Nous Research at no cost. Your real costs are model inference, the host it runs on, and any managed hosting you choose instead of running it yourself.

Does Hermes Agent remember previous conversations?

Yes. It keeps curated memory in files that survive restarts, so the agent accumulates context about you and your work instead of starting fresh on every message.

Which messaging platforms does it support?

More than twenty, including Telegram, Discord, Slack, WhatsApp, Signal, Matrix, Mattermost, email, SMS, and BlueBubbles. They all share the same gateway configuration.

Can I use my own model provider?

Yes. Anthropic, OpenAI, Google, OpenRouter, and any OpenAI-compatible endpoint are supported, and you can configure routing and fallbacks across them.

Do I need a server to run it?

Not to evaluate it. The desktop installer runs locally. A server or managed deployment becomes worthwhile once the assistant needs to be reachable by other people.

Key takeaways

Hermes Agent is a self-improving AI agent built by Nous Research. It runs as a long-lived assistant rather than a chat window: it keeps memory between sessions, loads skills, calls tools, and answers on the messaging platforms your team already uses. This page is the starting point. It covers what the agent actually is, which parts you have to run yourself, and which deployment path fits the work in front of you.
Start with one model, one channel, and one controlled test conversation.
Use managed hosting when deployment speed matters more than operating the server yourself.

Continue the setup

Blog guide

Hermes Agent Quickstart: Install and Run Your First Chat

Install Hermes Agent, choose a provider, run a first chat, and verify sessions work. A short quickstart that ends with proof, not with a green status light.

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Use case