Honcho Memory

Honcho adds AI-native memory to OpenClaw. 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 are persisted 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 that 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.

How it works

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

During conversation, Honcho tools query the service in the before_prompt_build phase, injecting relevant context before the model sees the prompt. This ensures accurate turn boundaries and relevant recall.

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

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