How to Configure OpenClaw Memory

📘 Guide status: This page explains OpenClaw’s memory system and how to configure persistent context and cross-session storage. For first-time setup, see the Quick Start Guide; for config file layout, see Configuration File Structure.

Overview

Unlike many cloud chatbots that reset context when you start a new chat, OpenClaw’s memory system keeps persistent context across all sessions and messaging platforms. Your agent can remember past conversations, preferences, and task history whether you talk to it on WhatsApp, Telegram, Discord, or Slack-so it can carry on long-running workflows and maintain continuity. This page covers where memory is configured, what options you can set, and how to tune it for your architecture and model limits.

This guide covers:

What the Memory System Does

OpenClaw’s memory gives your agent persistent context: it stores conversation history and relevant state so that:

  • Cross-session continuity: The agent remembers what you discussed in previous chats, so you can say “continue with that” or “remind me what we decided.”
  • Cross-channel consistency: Context can be shared across channels (e.g. you start on Telegram and later ask on Discord); the agent has one coherent view of the relationship.
  • Long-running tasks: Multi-step workflows (e.g. “research this topic and send me a summary tomorrow”) can rely on stored context instead of you repeating everything.

This is a core differentiator from cloud chatbots like ChatGPT or Claude web: OpenClaw runs on your infrastructure and keeps context under your control. For how this compares to other platforms, see OpenClaw vs ChatGPT and AI agent vs chatbot.

Where Memory Is Configured and Stored

Memory settings live in two places:

  1. Config file: The main OpenClaw config file (see Configuration File Structure) has a Memory section where you define global options: storage path, context length limits, retention rules, and similar. You edit it via openclaw config edit or by editing the file manually in the directory reported by openclaw doctor or openclaw status.
  2. Session / state data: The actual conversation context and memory data are stored on disk (e.g. in a session or state directory). That path is often configurable in the same Memory section-so you can choose where to store persistent data, back it up, or point it to a volume in Docker or on a VPS. For backup and security, treat this directory like important application state.

Exact key names and paths depend on your OpenClaw version. Always check the official OpenClaw documentation for the current schema.

Configuration Options

Typical options you can set in the Memory section (names may vary by version):

  • Context window / history length: How much conversation history to keep and send to the model (e.g. last N messages or tokens). Larger context improves coherence but increases latency and API cost; it is also limited by your model’s maximum context size (e.g. 200K tokens for some Claude models).
  • Retention / persistence: How long to keep context (e.g. forever, or expire after a period). Useful for privacy or to avoid unbounded growth.
  • Storage path: Directory for session and memory data. Ensure the process has read/write access and that you back it up if you care about continuity.
  • Per-agent memory: Whether each agent has its own memory or shares a global one. Multiple agents can have separate contexts (e.g. “support” vs “personal”) or share one; this is often configured under the agent block or in the Memory section.

Tuning memory affects performance: very long contexts mean more tokens per request and slower responses. Balance coherence with cost and latency; see Memory and context in the agent guide.

Step-by-Step Configuration

Step 1: Ensure OpenClaw is installed and running

You need a working OpenClaw installation. If you haven’t set it up yet, follow the Installation guide (e.g. Quick Start, Docker, or VPS). Then check status:

openclaw status

Step 2: Open the configuration file

Edit the main config file. Recommended:

openclaw config edit

Or open the config file manually at the path shown by openclaw doctor. For the full layout (gateway, channels, model providers, agents, skills, memory), see Configuration File Structure.

Step 3: Locate or add the Memory section

Find the Memory (or equivalent) section in the config. If it’s missing, add it according to the official docs for your version. Typical settings include storage path, context length (messages or tokens), and retention. Set the storage path to a directory that exists and is writable; for Docker, use a mounted volume if you want data to persist across container restarts.

Step 4: Adjust per-agent memory (optional)

If you use multiple agents, check whether each agent can override memory behavior (e.g. use global memory vs isolated context). Configure this in the agent blocks or as documented for your version.

Step 5: Restart and verify

Restart the gateway so changes take effect (e.g. openclaw gateway restart or restart the service). Then have a short conversation on a channel (e.g. Telegram), start a new session later, and confirm the agent still has context. If something goes wrong, see Troubleshooting and Common issues below.

Memory and Agents

Each agent can use the global memory system or have its own context. In the config, agents often reference memory settings (e.g. “use global memory” or “max context length”). Long context improves coherence but increases latency and cost; tune according to your performance needs and your model’s context limits. For full details, see Memory and Context in the agent customization guide.

Common Issues and Troubleshooting

Issue Solution
Memory not persisting across sessions Check that the Memory section exists and the storage path is writable; ensure the gateway was restarted after config changes. Verify disk space and permissions.
Context too long / slow or expensive Reduce context window (fewer messages or tokens) in the Memory or agent config. Align with your model’s max context; see model providers and performance tuning.
Storage path errors or permission denied Ensure the directory exists and the OpenClaw process has read/write access. On Docker, use a mounted volume with correct ownership.
Config validation failed after editing memory Check key names and types against the official schema; use openclaw doctor for diagnostics. See Troubleshooting and Configuration problems.

For more solutions, use openclaw doctor and the Troubleshooting guide.

Best Practices

  • Match context to model limits: Don’t set a context window larger than your model supports; excess tokens waste cost and can cause errors.
  • Back up session/memory data: If you rely on long-running context, back up the storage directory and include it in your security checklist and disaster recovery plan.
  • Privacy and retention: For sensitive use cases, consider shorter retention or separate memory per agent/channel; follow security best practices and any compliance requirements.
  • Monitor growth: Session and memory storage can grow; plan log rotation and disk space, and use monitoring and logging where appropriate.
  • Test after changes: After changing memory settings, test with a few conversations and a new session to confirm persistence and performance.

Next Steps

Related Resources