Companion agent

Companion Hub ships with a first-party AI agent ecosystem. The Choose your AI agent step of the onboarding wizard lets you pick OpenClaw (an open-source agent for coding and computer use) or Hermes (an advanced reasoning assistant for your tools, memory, and notifications), and configures models, remote access, and tool integration automatically. You can skip the step and add an agent later from the App Store.

OpenClaw

OpenClaw  is a self-hosted personal AI assistant with:

• Web-based chat interface
• Headless browser automation
• Tool and MCP integration with Hub

Install it from the App Store as OpenClaw WebCLI (ci-openclaw). Hub gives it the chat model, embedding model, and context size it resolved for your hardware, along with any cloud provider keys you saved in Settings → AI. OpenClaw supports OpenAI, Anthropic, Google Gemini, and other providers.

On a Hub install, ci-openclaw automatically receives Hub MCP credentials and loads the bundled ci-hub plugin on startup — no manual MCP configuration required. The agent can call Hub tools such as hub_list_installed_apps as soon as the container starts.

Hermes

Hermes is a messaging AI assistant available as a first-party marketplace app (ci-hermes). It ships a web terminal and dashboard, plus a messaging gateway for platform integrations (Slack, Discord, and more). Select it during the Onboarding wizard if you prefer its interaction model, or install it later from the App store.

On a Hub install, ci-hermes automatically registers mcp_servers.hub in its config against the Streamable HTTP endpoint (…/api/mcp) with Bearer auth, exposing all Hub hub_* tools alongside any optional Companion Memory MCP. The block carries no transport: key — the agent’s default Streamable HTTP client is correct, and a stale transport: sse line from an older install is removed on the next configuration pass.

OpenClaw and Hermes side by side

What this page documents for each agent. A blank cell means the page does not cover that point, not that the agent lacks it.

Companion Memory has its own chat

You do not need a separate agent app to talk to your memory. Companion Memory ships a Chat surface of its own, enabled by default, which runs against a local model and can call the same intent tools it publishes over MCP — so it answers from your own graph rather than from a general model’s guesses. Its default chat model is gemma4:e4b; you can point it at a different served model, or at an OpenAI-compatible endpoint instead of Ollama, from Settings → Model on the memory server.

OpenClaw and Hermes are for the jobs that chat is not: coding, computer use, messaging gateways, and running unattended.

Local vs cloud models

Agents can use:

• Local models through the engine you chose in Settings → AI: Ollama, vLLM, oMLX, or Lemonade
• Cloud providers (OpenAI, Anthropic, Google, GitHub Copilot)

Hub detects hardware and recommends models during setup. See AI and inference for Ollama installation, GPU setup, and standardized inference variables.

Remote access for agents

During onboarding, choose how to reach your agent remotely:

• Private VPN — reach your Hub from your other devices over Tailscale
• Web — a private link you can open in any browser, through the Cloudflare Gateway (requires CI Account pairing)

MCP server

Hub exposes an MCP (Model Context Protocol) server at /api/mcp that agents can connect to. It speaks Streamable HTTP and offers about 80 hub_* tools for installing, configuring, backing up, and monitoring apps. MCP is enabled by default — the server loads automatically unless you explicitly set MCP_ENABLED=false.

No API key is created for you. Credentials are minted explicitly from Settings → Security, and the key is shown once at creation — enabling MCP and holding a working credential are separate steps. Each key also has a capability: Read-only, Read & write, or Read, write & delete, which decides what its tools may change.

The Settings → MCP tab shows whether the server is enabled, its endpoint, how many tools it offers, and how many sessions are connected. It also lists your keys, lets you browse the tool catalog, and lists the MCP server apps you have installed. You can run a tool from the catalog with JSON arguments to see what it does. Destructive tools ask you to confirm first.

The server stays on unless MCP_ENABLED is false. cihub mcp setup, cihub mcp shutdown, and cihub mcp config set or print that variable in the env file of the current folder (.env.local by default), so they apply to a source checkout. On an installed Hub they don’t read or change the Hub’s own env file. Check status in Settings → MCP, and list your keys with cihub api-key list.

Agent apps with hub_integration.mcp_client: true in their manifest automatically receive these in their environment:

An app with hub_integration.mcp_client: true publishes its host port on 127.0.0.1 only, because it holds a key that can drive your Hub. To reach an agent’s web interface from another device, use Private VPN or Public Web.

How those pieces fit together once the agent container is running:

flowchart LR
    A["Agent app<br/>ci-openclaw or ci-hermes"] -->|"HUB_MCP_URL<br/>Bearer HUB_MCP_API_KEY"| M["Hub MCP endpoint<br/>ci-hub:5002/api/mcp"]
    M --> T["hub_* tools<br/>e.g. hub_list_installed_apps"]
    A -.->|"optional"| CM["Companion Memory MCP"]
    A -->|"local models"| O["Ollama<br/>Settings → AI"]
    A -->|"cloud providers"| P["OpenAI, Anthropic,<br/>Google, GitHub Copilot"]

Building agent apps

To publish an agent to the marketplace:

1. Build a container (see Static Container Builder)
2. Set hub_integration.mcp_client: true and optional hub_integration.inference in config.json
3. Submit via ci.computer/store-submit