June 9, 2026 · 6 min read

Give your OpenClaw agent permanent memory with Vilix

OpenClaw forgets everything between reboots and across channels. Connect Vilix as its MCP brain and it gains permanent, cross-channel memory so every action starts with full context.

OpenClaw is a self-hosted always-on agent that listens across WhatsApp, Telegram, Slack, Discord, Signal, and iMessage, runs shell commands, and schedules tasks on your behalf. The problem is that every reboot wipes its context, and a message sent via Telegram arrives with no memory of the conversation you had yesterday via Slack. Connect Vilix as its MCP brain and both problems disappear: OpenClaw gets a persistent, cross-channel memory layer that survives restarts and follows you across every channel it supports.

Why OpenClaw needs external memory

OpenClaw is designed to run indefinitely in the background, but its in-process state is ephemeral. When the process restarts, whether from a server reboot, a crash, or a deliberate redeploy, prior conversation threads are gone. Worse, each channel arrives as an independent context, so a preference you set over Slack is invisible when you message the agent through Telegram an hour later.

What OpenClaw needs is exactly what Vilix provides: a server-side store that holds conversation history, project state, and personal rules, and that any tool (or any channel) can read from and write to via a standard MCP connection. Because Vilix memory is tied to your account rather than to any one process or channel, it is naturally cross-channel and reboot-safe.

How the Vilix MCP tools work

Vilix exposes two core tools that you wire around each agent action. Before OpenClaw acts on a message, it calls get_context with that message as input. Vilix responds with recent conversation history, your saved memories, related threads from past conversations, any active project and task state, and your personal user_rules (short style directives like "prefer shell one-liners" or "respond in French"). After OpenClaw completes the action and replies, it calls save_turn to persist both the input and the output. The next message, from any channel, starts with that full context already loaded.

This is the same mechanism described in how to add memory to any agent with Vilix MCP. OpenClaw is one of the supported tools that takes a custom MCP connector, so no special adapter is required.

Connecting Vilix to OpenClaw

OpenClaw reads its MCP configuration from the same JSON format used by other MCP-aware tools. Add the following block to your OpenClaw MCP config file (or the equivalent section in your config.json):

{
  "mcpServers": {
    "vilix": {
      "url": "https://api.vilix.ai/mcp",
      "transport": "sse"
    }
  }
}

Restart OpenClaw. On first use it will prompt you to authenticate with your Vilix account. After that, the get_context and save_turn tools are available to the agent alongside any other MCP tools you have configured. See the Vilix MCP docs for full connector reference, including how to pass an API token directly if your deployment environment cannot complete an interactive auth flow.

Wiring the tools into your agent loop

If you are running OpenClaw with a custom system prompt or tool-selection policy, add explicit instructions to call Vilix before and after each action. A minimal prompt addition looks like this:

Before taking any action, call get_context with the user message.
After sending a reply, call save_turn to persist the exchange.
Use source: "OpenClaw" and reuse the chat_id from the current session.

With that in place, OpenClaw will automatically load prior context (including which tasks are open, what the user's preferences are, and what happened in the last session) and write back after each turn. A future demo video will show this loop running live across a Telegram and Slack session, surviving a process restart between the two. That slot is reserved here once the recording is ready.

What the agent remembers

After a few sessions through Vilix, OpenClaw carries three kinds of persistent state:

Conversation history with semantic and keyword search, so it can surface what you discussed three weeks ago as long as the topic is relevant.
Projects and tasks with live state that auto-injects into context, so "what is left on the deploy checklist" works without you repeating it.
User rules, short personal directives you set once and the agent applies across every channel and every tool in your stack.

Because that memory lives in your Vilix account, the same context is available to ChatGPT, Claude, Cursor, and any other connected tool. OpenClaw is no longer an island. Learn more about how cross-AI memory works across your whole stack.

A note on sandbox and prompt injection

OpenClaw can execute shell commands and schedule tasks, which makes prompt injection a real threat. A malicious message on any channel that reaches the agent could attempt to exfiltrate data or run unintended commands by embedding instructions in the message text. Keep OpenClaw sandboxed (network-isolated execution environment, restricted shell user, no root access), review what tools and shell permissions you expose to it, and treat any external input, including incoming messages, as untrusted. Vilix memory itself is write-once per turn from your authenticated account, so it is not an injection vector, but the agent loop that reads from it can be.

Getting started

If you do not have a Vilix account yet, try Vilix free (the Pro trial is seven days, no card required). Connect it to OpenClaw using the JSON snippet above, add the two-line prompt addition to your agent loop, and your always-on agent will remember everything from the first message forward, across every channel, across every restart.

Frequently asked questions

Does Vilix officially support OpenClaw?

Yes. OpenClaw supports custom MCP connectors and Vilix exposes a standard MCP endpoint at api.vilix.ai/mcp. No custom adapter is needed. Any tool that accepts a custom MCP server can connect to Vilix the same way.

Will OpenClaw memory survive a server reboot?

Yes. Memory is stored server-side in your Vilix account, not in OpenClaw's process. A reboot, crash, or redeploy does not affect it. The next session picks up exactly where the last one left off as soon as OpenClaw calls get_context.

Does memory work across WhatsApp, Telegram, Slack, and Discord at once?

Yes. Vilix memory is keyed to your account, not to any channel. OpenClaw calling get_context from a Telegram message sees the same history as a call originating from Slack or Discord. The agent builds a unified view across all channels automatically.

Is it safe to give an always-on agent access to persistent memory?

Memory access is not the primary risk. The risk is prompt injection via incoming messages that try to hijack the agent's shell or task execution. Run OpenClaw in a sandboxed environment with a restricted shell user, limit the tools and permissions it has, and treat all external input as untrusted regardless of the channel it arrives on.

How is this different from just saving logs to a file?

Log files grow without bound and require the agent to scan and parse them on every turn. Vilix uses semantic and keyword search to retrieve only the most relevant prior context, keeps project and task state separately for instant structured access, and makes the same memory available to every other AI tool in your stack, not just OpenClaw.