# For MacOS/Linux
curl -fsSL https://raw.githubusercontent.com/tinyhumansai/openhuman/main/scripts/install.sh | bash

# For Windows
irm https://raw.githubusercontent.com/tinyhumansai/openhuman/main/scripts/install.ps1 | iex

What is OpenHuman?

OpenHuman is an open-source agentic assistant designed to integrate with you in your daily life. Each bullet links to the deeper writeup in the docs.

Simple, UI-first — A clean desktop experience and short onboarding paths so you can go from install to a working agent in a few clicks, without a config-first setup. No terminal required.
One subscription, many providers — One account gets you access to many agentic APIs (AI models, search, webhooks/tunnels, third-party APIs).
118+ third-party integrations — Plug into Gmail, Notion, GitHub, Slack, Stripe, Calendar, Drive, Linear, Jira and the rest of your stack with one-click OAuth. Every connection is exposed to the agent as a typed tool.
Memory Tree + Obsidian Wiki — A local-first knowledge base built from your data and your activity. Everything you connect is canonicalized into ≤3k-token Markdown chunks, scored, and folded into hierarchical summary trees stored in SQLite on your machine. The same chunks land as .md files in an Obsidian-compatible vault you can open, browse and edit — inspired by Karpathy's obsidian-wiki workflow.
Auto-fetch from your stack — Every five minutes the core walks each active connection and pulls fresh data into the memory tree. No prompts, no polling loops you have to write — the agent already has tomorrow's context this morning.
Smart token compression (TokenJuice) — Verbose tool output (git, npm, cargo, docker, large emails) is compacted by a rule overlay before it ever enters LLM context. Sweeping through thousands of emails stays cheap because the model never sees the noise.
Automatic model routing — Tasks pick their model. hint:reasoning lands on a strong reasoning model, hint:fast on a fast one, vision goes to a vision model — all under one subscription, with zero per-provider key juggling.
Native voice (ElevenLabs) — STT in, ElevenLabs TTS out, with mascot lip-sync. Includes a live Google Meet agent that listens, takes notes and can speak back in your meetings.
Native search, scraper and coder — Built-in web search, web-fetch scraper, and a full filesystem / git / lint / test / grep toolset wired into the agent out of the box. No "install a plugin to read files" friction.
Optional local AI (via Ollama) — Off by default. Opt in per-workload to keep memory embeddings, summary-tree building, and background reflection loops on your machine. Chat / vision / voice stay cloud — the local path is scoped to the workloads where on-device actually pays.
Messaging channels, teams & orgs, privacy & security — Inbound/outbound across the channels you already use, shared workspaces for collaborating with an agent across a team, and workflow data that stays on device, encrypted locally, treated as yours.

For contributors: Architecture · Getting Set Up · Cloud Deploy · CONTRIBUTING.md.

OpenHuman vs Other Agent Harnesses

High-level comparison (products evolve—verify against each vendor). OpenHuman is built to minimize vendor sprawl, keep workflow knowledge on-device, and give the agent a persistent memory of your data — not only chat.

	Claude Cowork	OpenClaw	Hermes Agent	OpenHuman
Open-source	🚫 Proprietary	✅ MIT	✅ MIT	✅ GNU
Simple to start	✅ Desktop + CLI	⚠️ Terminal-first	⚠️ Terminal-first	✅ Clean UI, minutes
Cost	⚠️ Sub + add-ons	⚠️ BYO models	⚠️ BYO models	✅ One sub + TokenJuice
Memory	✅ Chat-scoped	⚠️ Plugin-reliant	✅ Self-learning	🚀 Memory Tree + Obsidian vault
Integrations	⚠️ Few connectors	⚠️ BYO	⚠️ BYO	🚀 118+ via OAuth
Auto-fetch	🚫 None	🚫 None	🚫 None	✅ 5-min sync into memory
API sprawl	🚫 Extra keys	🚫 BYOK	🚫 Multi-vendor	✅ One account
Model routing	🚫 Single model	⚠️ Manual	⚠️ Manual	✅ Built-in
Native tools	✅ Code-only	✅ Code-only	✅ Code-only	✅ Code + search + scraper + voice

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