Observe
See the plan, active cycle, tool activity, and result as it happens.
Designed as a system
Every mode of work shares the same context and controls.
Chat, goal loops, and automation use the same context engine, approvals, skills, apps, and durable state.
- One local gateway
- One web dashboard
- One inspectable home directory
Agentic chat
Conversation that can become work.
Run tools with approval controls, organize sessions, branch from earlier turns, compare answer variants, and tune model or memory behavior per conversation.
- Session fork and undo
- Folders, tags, and kanban
- Temporary and incognito memory modes
- Per-session model overrides
Autonomous goals
The agent keeps going. You keep the final say.
Intervene
Pause, nudge, resume, or stop without losing the accumulated run state.
Bound
Deterministic supervisors and approval modes constrain autonomous action.
Durable context
Memory and knowledge do different jobs.
PersonalClaw keeps learned personal context separate from the source material you deliberately add. Both remain inspectable.
Memory learns how you work.
Semantic, episodic, and procedural layers support recall, correction learning, and promotion of repeated facts.
Knowledge keeps the source.
Ingest documents, web pages, and media; enrich them with entities and make them searchable from chat.
Automation
Let the system notice first.
Schedule recurring work, react to webhooks, monitor connected channels, and dispatch background subagents without building a second automation stack.
- Cron, interval, and webhook triggers
- Channel inbox and drafted replies
- Background subagents
- Automatically matched workflow SOPs
Bring the right agent
Native, ACP, or app-defined.
PersonalClaw can run its native agent or connect external coding agents through ACP. Claude Code, OpenAI Codex, and Kiro CLI remain behind the same host approval boundary.
Explore agent apps
Multiple runtimes ACP boundary Shared context Replaceable providers
Runs safely on its own
Autonomy with a floor under it.
Before you hand the system unattended work, it gives you the controls to trust it: a kill switch that suspends every automation at once, daily spend ceilings, outbound secret scanning, and per-provider circuit breakers. Interactive chat is never affected.
- Incident kill switch, explicit resume
- Token and dollar budgets per day and per run
- Outbound prompt scanning: warn, redact, or block
- Named safety profiles for unattended runs
Diagnoses itself
See what's healthy, and fix what isn't.
The Doctor runs read-only health probes across every subsystem — memory, channels, local models, app backends, the SPA, model-provider breakers. A degraded capability is never mistaken for a dead gateway, confirm-gated fixes repair the common faults, and a health-scored engine keeps the stores tidy on its own.
- Tiered probes with per-capability evidence
- No-model degraded mode, stated plainly
- Confirm-gated repairs and crash capture
- Health-scored self-maintenance
Open source · self-hosted
Run the system on your machine.
Python 3.12, an aiohttp gateway, React dashboard, SQLite state, and no product telemetry.