Early Beta: Under active development. Expect rough edges.

OpenHuman is not AGI. But it is a meaningful architectural step closer, with better memory, better orchestration, and better tooling.

🎉 Within one week of launch, OpenHuman became the number one trending repository on GitHub for nine days in a row.

Install

Download installers from tinyhumans.ai/openhuman or from the GitHub Releases page.

For terminal installs (Homebrew, Debian/Ubuntu .deb, AUR, install scripts, and platform notes), see INSTALL.md.

What is OpenHuman?

OpenHuman is three things most assistants aren't: a brain that builds a persistent, local memory of your world; a fantastic orchestrator that runs fleets of agents on durable graphs; and a deep researcher that sweeps your data and the web before you finish asking. Every bullet links to the deeper writeup in the docs.

🧠 The brain

• Memory Tree + Obsidian Wiki: your data compressed into scored Markdown trees in SQLite on your machine, mirrored as an Obsidian vault you can open and edit. No vector-soup black box.
• 100+ OAuth integrations, 5,000+ MCP servers, 90,000+ Skills: one click into Gmail, Notion, GitHub, Slack and the rest of your stack. Auto-fetch feeds the brain every 20 minutes, so it has tomorrow's context this morning.
• A subconscious: a background loop that diffs your world, advances your goals, and writes your morning briefing. Thinking continues after you stop typing.
• Goals & Todos: long-term goals, durable per-thread goals, and a shared kanban board per conversation.
• TokenJuice: tool output compressed before it hits the model: same information, up to 80% fewer tokens. A brain this big would be unaffordable without it.

🕸️ The orchestrator

• Workflows: the agent proposes the automation; you review it on a canvas and save. Durable, trigger-driven, approval-gated runs on open-source tinyflows.
• A harness that finishes the job: checkpointed graph runs on open-source tinyagents. Stuck agents get steered, halted ones return a root cause, and every run replays with real per-call costs.
• A split brain, always on: a fast reflex agent triages inbound traffic while a deep reasoning core delegates to worker fleets, steered by the subconscious.
• An agent economy: a @handle on tiny.place, Signal-encrypted agent-to-agent orchestration, x402 USDC bounties and trading. Keys never touch disk.

🔬 The deep researcher & doer

• SuperContext: a research scout sweeps your memory and files before the model reads your first message. No cold starts.
• Batteries included: web search, scraper, coder toolset, a real browser, and native voice with in-process Whisper. Model routing picks the right LLM per workload on one subscription, with local AI optional.
• Meeting agents: joins Meet, Zoom, Teams, and Webex with a face and a voice. It auto-joins from your calendar, streams a live transcript, answers by name, and files a summary with action items.
• Image & video generation: Seedream/SeedEdit images and Seedance/Veo video, straight into your workspace on the same subscription.
• 17 messaging channels: Telegram, Discord, Slack, WhatsApp, Signal, iMessage… plus native email (IMAP IDLE + SMTP). Your agent reaches you where you already are.

🧍 Human, private, yours

• Simple, UI-first & Human: install to working agent in a few clicks, with no config files and no terminal. And it has a face: a mascot that speaks, reacts, and remembers you.
• Privacy & security: on-device encrypted data, approval gate, OS-keyring secrets, and opt-in sandboxing. There is also Privacy Mode: flip one switch and no inference leaves your machine, enforced in the Rust core.
• Themes & Theme Studio: five theme families plus a full visual editor, exportable as JSON.

Context in minutes, not weeks

OpenHuman is the first agent harness that gets to know you in minutes. Inspired by Karpathy's LLM Knowledgebase. Most agents start cold. Hermes learns by watching you work; OpenClaw waits for plugins to ferry context in. Either way, you spend days or weeks before the agent knows enough about your stack to be genuinely useful.

OpenHuman summarizes and compresses all your documents, emails & chats; and creates a memory graph that lets your agent remember everything about you.

OpenHuman skips the wait. Connect your accounts, let auto-fetch pull data locally on a 20-minute loop, and then have Memory Trees compress everything into Markdown files stored intelligently in a Karpathy-style Obsidian wiki.

In just one sync pass, the agent has full (compressed) context of your inbox, your calendar, your repos, your docs, your messages. No training period. No "give it a few weeks.". It becomes you, controlled by you.

Already self-host agentmemory across other coding agents? OpenHuman ships an optional Memory backend that proxies to it. Set memory.backend = "agentmemory" in config.toml and the same durable store powers OpenHuman alongside Claude Code, Cursor, Codex, and OpenCode. See the agentmemory backend page for setup.

An orchestrator, not a chatbot

Most agent harnesses run one agent in one loop. OpenHuman is an orchestrator:

Agent-to-agent messaging runs over Signal-protocol end-to-end encryption, so you can connect anything (Claude Code, Codex, OpenClaw, Hermes) and use OpenHuman to orchestrate all of your agents and tools.

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