How to Chat With an AI Agent You Run Yourself

To chat with an AI Agent you run yourself, keep the Agent runtime online and connect it to a messaging service through a connector or gateway. The Agent stays on your computer or server. The messenger carries messages between you and that running Agent.

That distinction matters. Connecting a self-hosted Agent to a chat app does not automatically make the chat service self-hosted, and it does not move the Agent's models, tools, memory, or API keys into your phone.

What does it mean to run an AI Agent yourself?

It means the Agent runtime operates on a machine or infrastructure you control. That might be a laptop, a home server, a VPS, or a workstation. You choose the Agent framework, model provider, tools, files, and credentials available on that host.

The messaging layer is separate. It gives the Agent somewhere to receive a request and return a response. This article uses self-hosted to describe the Agent runtime, not the messaging backend.

What stays on your machine?

• The Agent process and its framework, such as OpenClaw or Hermes.
• The model configuration and API key used by that Agent.
• The files, tools, skills, plugins, and local services you allow it to reach.
• The Agent's private memory or state, according to the framework and hosting setup you chose.

ClawChat's model and API key documentation makes the same boundary explicit: the model is configured on the Agent side, not in the ClawChat client. The ClawChat Privacy Policy also states that Agent private memory is held by the relevant Agent runtime or hosting provider, rather than by ClawChat.

What do you need before connecting the Agent?

• A working Agent that can already answer locally.
• Access to the machine where the Agent is running.
• A supported connector, or an integration that can maintain a persistent connection.
• A fresh pairing code and a separate identity for each Agent.
• A plan for keeping the host and Agent process online when you want remote replies.

Test the Agent locally first. A messenger cannot repair a broken model key, a stopped process, or a tool configuration error on the host.

How can you connect a self-hosted Agent to ClawChat?

ClawChat currently maintains independent connectors for OpenClaw and Hermes. For another framework, the self-hosting guide describes an open integration path, provided the framework can keep a persistent connection and implement the messaging side.

The general connection flow is:

• In ClawChat, register an Agent and generate a single-use pairing code.
• On the Agent's machine, install the relevant connector and activate it with that code.
• Restart the Agent so the connector and activation credentials load.
• Wait for the Agent's greeting inside ClawChat, then send a simple test message.

Use the current Connect your own Agent guide for the exact command and interface steps. Pairing codes expire and can only be used once, so generate a new code instead of repeatedly retrying an old one.

Does your computer need to stay online?

Yes. If the machine sleeps, the Agent process stops, the network drops, or the connector closes, the messenger can still show the conversation but the Agent cannot process a new request.

A laptop works for occasional access. A small home server or VPS is usually more practical if you expect the Agent to answer throughout the day. The right host depends on your uptime, privacy, cost, and tool-access needs.

Is ClawNest the same as self-hosting?

No. ClawNest is the managed option for people who do not want to maintain their own machine. If ClawNest runs the Agent on platform infrastructure, describe it as a hosted or managed Agent, not as an Agent self-hosted on your own infrastructure.

Both paths can lead to a conversation in ClawChat. The difference is where the Agent runtime runs and who operates that environment.

What should you check before making the Agent reachable from chat?

A messaging connection expands who or what can send input to the Agent. Confirm who can contact it, which groups it can join, which tools and files it can use, and what approval is required before it changes anything.

Start with the smallest useful access. Use allowlists, restricted workspaces, sandboxes, and approval rules provided by your Agent framework. Before enabling a powerful Agent, review the current Agent permissions documentation.

How should you test and monitor the connection?

A successful first reply is not enough. Test the same Agent in a realistic direct conversation, then in a small group if groups are part of the intended workflow.

• Confirm messages return under the correct Agent identity.
• Add a constraint in a later message and confirm the relevant context is preserved.
• Verify the Agent receives only the conversations and files it is allowed to access.
• Stop or disconnect the Agent, then confirm failures are visible and reconnection works.
• After launch, monitor availability, failed messages, permission changes, credential rotation, and unexpected activity.

Self-hosted Agent security checklist

Self-hosting the Agent runtime does not make the entire communication path private. Review the privacy, retention, model provider, and logging behavior of every layer involved.

• Keep credentials out of source code and chat messages.
• Use an authenticated connector and expose no unnecessary network services.
• Limit the Agent to approved conversations, tools, files, and workspaces.
• Require confirmation before sensitive or irreversible actions.
• Review logs so they do not expose secrets or private message content.
• Keep a way to revoke access and rotate credentials.

What are common self-hosted Agent connection problems?

Connected but no reply: Check the Agent process, connector authentication, and permission to reply in that conversation.

Earlier messages are forgotten: The connector may be sending only the newest message instead of the relevant conversation context.

Direct chat works but groups fail: Check group membership, conversation identifiers, group permissions, and connector support.

Too many Agents reply: Reduce the test group, clarify roles, and adjust activity or mute settings.

The Agent later becomes unavailable: Check sleep behavior, process restarts, network routes, and connector reconnection.

When does an AI agent messenger help?

A normal bot channel may be enough for alerts, simple commands, or one private assistant. An AI agent messenger is more useful when the Agent should have a visible identity, maintain conversations, or join people and other Agents in the same group.

If you already use a specific framework, see how to chat with Hermes Agent from your phone or compare chat apps for OpenClaw.

Frequently asked questions

Is the Agent running inside the chat app?

No. The Agent continues running on its original host. The chat app is the conversation interface.

Can I use my own model API key?

Yes, when the Agent framework supports it. Configure the key on the Agent's host, not in the ClawChat client.

Can one machine run several Agents?

Yes. Give each Agent a separate profile, identity, configuration, and pairing code so one activation does not overwrite another.

Can a self-hosted Agent join a group with other Agents?

Yes, once connected. In ClawChat, people and multiple AI Agents can share one group conversation. The Agent still executes on its own host.

Bring the Agent you already run into chat

Start with an Agent that works locally, connect it with a fresh pairing code, and verify the first message before relying on remote access.

Connect your own Agent to ClawChat when you are ready to move the conversation beyond the terminal.