Honcho Memory: AI-Native Cross-Session Memory Plugin

Learn how the Honcho plugin provides AI-native cross-session memory for OpenClaw agents. This guide covers user modeling, semantic search, and multi-agent awareness for developers building persistent conversational AI.

Read this when

  • You want persistent memory that works across sessions and channels
  • You want AI-powered recall and user modeling

Honcho brings AI-native memory to OpenClaw through an external plugin. It saves conversations to a dedicated service and builds user and agent profiles over time, giving your agent cross-session context that goes beyond workspace Markdown files.

What it provides

  • Cross-session memory - conversations are saved after each turn, so context persists across session resets, compaction, and channel changes.
  • User modeling - Honcho keeps a profile for each user (preferences, facts, communication style) and for the agent (personality, learned behaviors).
  • Semantic search - search across observations from past conversations, not just the current session.
  • Multi-agent awareness - parent agents automatically track spawned sub-agents, with parents added as observers in child sessions.

Available tools

Honcho registers tools the agent can use during conversation:

Data retrieval (fast, no LLM call):

ToolWhat it does
honcho_contextFull user representation across sessions
honcho_search_conclusionsSemantic search over stored conclusions
honcho_search_messagesFind messages across sessions (filter by sender, date)
honcho_sessionCurrent session history and summary

Q&A (LLM-powered):

ToolWhat it does
honcho_askAsk about the user. depth='quick' for facts, 'thorough' for synthesis

Getting started

Install the plugin and run setup:

openclaw plugins install @honcho-ai/openclaw-honcho
openclaw honcho setup
openclaw gateway --force

The setup command asks for your API credentials, writes the config, and optionally migrates existing workspace memory files.

Info

Honcho can run entirely locally (self-hosted) or through the managed API at api.honcho.dev. No external dependencies are needed for the self-hosted option.

Configuration

Settings are located under plugins.entries["openclaw-honcho"].config:

{
  plugins: {
    entries: {
      "openclaw-honcho": {
        config: {
          apiKey: "your-api-key", // omit for self-hosted
          workspaceId: "openclaw", // memory isolation
          baseUrl: "https://api.honcho.dev",
        },
      },
    },
  },
}

For self-hosted instances, point baseUrl to your local server (for example http://localhost:8000) and leave out the API key.

Migrating existing memory

If you have existing workspace memory files (USER.md, MEMORY.md, IDENTITY.md, memory/, canvas/), openclaw honcho setup detects them and offers to migrate them.

Info

Migration is non-destructive - files are uploaded to Honcho. Originals are never deleted or moved.

How it works

After every AI turn, the conversation is saved to Honcho. Both user and agent messages are observed, letting Honcho build and refine its models over time.

During conversation, Honcho tools query the service during OpenClaw's before_prompt_build plugin hook, injecting relevant context before the model sees the prompt.

Honcho vs builtin memory

Builtin / QMDHoncho
StorageWorkspace Markdown filesDedicated service (local or hosted)
Cross-sessionVia memory filesAutomatic, built-in
User modelingManual (write to MEMORY.md)Automatic profiles
SearchVector + keyword (hybrid)Semantic over observations
Multi-agentNot trackedParent/child awareness
DependenciesNone (builtin) or QMD binaryPlugin install

Honcho and the builtin memory system can work together. When QMD is configured, additional tools become available for searching local Markdown files alongside Honcho's cross-session memory.

CLI commands

openclaw honcho setup                        # Configure API key and migrate files
openclaw honcho status                       # Check connection status
openclaw honcho ask <question>               # Query Honcho about the user
openclaw honcho search <query> [-k N] [-d D] # Semantic search over memory

Further reading