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):
Q&A (LLM-powered):
Getting started
Install the plugin and run setup: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 underplugins.entries["openclaw-honcho"].config:
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’sbefore_prompt_build plugin hook, injecting relevant context before the model
sees the prompt.
Honcho vs builtin memory
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.