adolf/docs/concepts/memory-honcho.md

summary, title, read_when

summary	title	read_when
AI-native cross-session memory via the Honcho plugin	Honcho memory	You want persistent memory that works across sessions and channels You want AI-powered recall and user modeling

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

What it provides

• Cross-session memory - conversations persist after every turn, so context carries across session resets, compaction, and channel switches.
• User modeling - Honcho maintains a profile for each user (preferences, facts, communication style) and for the agent (personality, learned behaviors).
• Semantic search - search over 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):

Tool	What it does
honcho_context	Full user representation across sessions
honcho_search_conclusions	Semantic search over stored conclusions
honcho_search_messages	Find messages across sessions (filter by sender, date)
honcho_session	Current session history and summary

Q&A (LLM-powered):

Tool	What it does
honcho_ask	Ask 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 prompts for your API credentials, writes the config, and optionally migrates existing workspace memory files.

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

Configuration

Settings live 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 omit 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 and offers to migrate them.

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 persisted 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 / QMD	Honcho
Storage	Workspace Markdown files	Dedicated service (local or hosted)
Cross-session	Via memory files	Automatic, built-in
User modeling	Manual (write to MEMORY.md)	Automatic profiles
Search	Vector + keyword (hybrid)	Semantic over observations
Multi-agent	Not tracked	Parent/child awareness
Dependencies	None (builtin) or QMD binary	Plugin 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

• Plugin source code
• Honcho documentation
• Honcho OpenClaw integration guide

Related

• Memory overview
• Builtin memory engine
• QMD memory engine
• Context Engines