> ## Documentation Index
> Fetch the complete documentation index at: https://clawhqplatform.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Hermes

> ClawHQ's conversational AI layer — persistent memory, skills, and long-term context.

Hermes is the primary conversational agent in ClawHQ. While OpenClaw agents (Mike, Scout, Codex, etc.) are specialized execution engines triggered by commands, Hermes is the always-on brain — it holds context across every conversation, remembers your team, your goals, and past interactions, and gets smarter the more you use it.

Hermes is built on the [Nous Research](https://nousresearch.com) Hermes model series and runs as its own service alongside OpenClaw.

## Hermes vs OpenClaw agents

|              | Hermes                                                 | OpenClaw agents                                |
| ------------ | ------------------------------------------------------ | ---------------------------------------------- |
| **Purpose**  | Conversational AI, memory, NL interface                | Task execution, automation                     |
| **Memory**   | Persistent across all sessions                         | Per-conversation (configurable)                |
| **Triggers** | Always listening in connected channels                 | Keyword or command triggers                    |
| **Model**    | Single configurable model (`HERMES_MODEL`)             | Model Router — right model per task            |
| **Best for** | "What's going on?", complex Q\&A, long-running context | "Research X", "Code review Y", scheduled tasks |

Think of it this way: Hermes is your AI colleague you talk to every day. OpenClaw agents are specialists you bring in for specific jobs.

## Setup

Hermes starts automatically with `docker compose up`. The only required config is an API key for your chosen model provider.

### Environment variables

Add these to your `.env` file:

```bash theme={null}
# Required — model for Hermes to use
HERMES_MODEL=anthropic/claude-sonnet-4-6

# Required — at least one channel token
HERMES_DISCORD_BOT_TOKEN=your-discord-bot-token

# Optional — additional channels
HERMES_TELEGRAM_BOT_TOKEN=your-telegram-bot-token
HERMES_SLACK_BOT_TOKEN=your-slack-bot-token
HERMES_SLACK_APP_TOKEN=your-slack-app-token

# Optional — port (default: 4300)
HERMES_PORT=4300
```

<Note>
  Hermes needs its **own bot tokens** — separate from the OpenClaw bot. Create a second Discord application at [discord.com/developers](https://discord.com/developers/applications) for Hermes. Having two bots lets you address them independently in Discord (`@Hermes` vs `@Mike`).
</Note>

### Supported models

Hermes uses a single model configured via `HERMES_MODEL`. Use any model string in `provider/model` format:

| Provider       | Example value                                    |
| -------------- | ------------------------------------------------ |
| Anthropic      | `anthropic/claude-sonnet-4-6`                    |
| OpenAI         | `openai/gpt-4o`                                  |
| OpenRouter     | `openrouter/nousresearch/hermes-3-llama-3.1-70b` |
| Groq           | `groq/llama-3.3-70b-versatile`                   |
| Local (Ollama) | `ollama/llama3.2`                                |

The recommended default is `anthropic/claude-sonnet-4-6` — fast, capable, and cost-effective for conversational use.

## Talking to Hermes

Once configured and your bot is invited to your Discord server:

```
@Hermes what's on my plate today?
```

```
@Hermes summarize what we discussed about the launch last week
```

```
@Hermes remember that the Q2 target is $50k MRR
```

Hermes automatically retrieves relevant context from memory before every response — you don't need to re-explain things you've already told it.

## Memory

Hermes stores conversation history in SQLite and uses semantic search to retrieve relevant past context before each reply. This happens automatically.

You can interact with memory directly:

| Command                                  | What it does                         |
| ---------------------------------------- | ------------------------------------ |
| `@Hermes remember [fact]`                | Stores something explicitly          |
| `@Hermes forget [topic]`                 | Removes memory entries about a topic |
| `@Hermes what do you know about [topic]` | Shows what Hermes has stored         |

Memory is per-deployment — shared across all team members using the same ClawHQ instance.

## Skills

Hermes can load skills from `~/.openclaw/skills/`. Skills extend what Hermes can do — web search, calendar access, file operations, custom integrations.

To see loaded skills:

```
@Hermes what skills do you have?
```

Skills are installed via the OpenClaw CLI or by dropping YAML files into the skills directory. See the [Skills reference](/reference/agent-config#skills) for the schema.

## Dashboard

Hermes activity is visible in the ClawHQ dashboard under **Team → Hermes**. From there you can:

* View conversation history
* See which skills are loaded
* Adjust the model
* Clear or export memory

## Next steps

<CardGroup cols={2}>
  <Card title="Connect Discord" icon="discord" href="/channels/discord">
    Set up a dedicated Hermes bot in Discord
  </Card>

  <Card title="Model Router" icon="route" href="/guides/model-router">
    How OpenClaw agents route tasks to the right model
  </Card>

  <Card title="First Agent" icon="robot" href="/guides/first-agent">
    Configure a specialized OpenClaw agent
  </Card>

  <Card title="Environment Variables" icon="gear" href="/reference/environment-variables">
    Full list of Hermes config options
  </Card>
</CardGroup>