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):
| 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 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 / 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