CowAgent is your own open-source personal AI agent. It plans tasks proactively, uses tools, skills and MCP, and gets to know you over time through long-term memory, a knowledge base and self-evolution. It's also an open, extensible Agent Harness.
CowAgent is multi-model, multi-channel and multi-agent, lightweight and built to extend. Plug in any major LLM provider, run it 24/7 on your computer or server, and reach it from the web and all major IM platforms.
🎬 Demo
🌟 Highlights
| Capability | Description |
|---|
| Planning | Decomposes complex tasks and executes them step by step, looping over tools until the goal is reached |
| Multi-Agent | Build a team of Agents, each with its own role, model, skills, and knowledge, collaborating within a shared conversation |
| Memory | Three-tier architecture (context → daily → core), automatic Deep Dream distillation, hybrid keyword + vector retrieval |
| Knowledge | Auto-curates structured knowledge into a Markdown wiki, builds an evolving knowledge graph with visual browsing |
| Evolution | Self-Evolution reviews conversations automatically to improve skills, follow up on unfinished tasks, and consolidate memory and knowledge, growing through everyday use |
| Skills | One-click install from Skill Hub, GitHub, ClawHub; or create custom skills via natural-language conversation |
| Tools | Built-in file I/O, terminal, browser, scheduler, memory retrieval, web search, and 10+ more tools — with native MCP integration |
| Channels | Integrates with Web, WeChat, Feishu, DingTalk, WeCom, QQ, Official Accounts, Telegram, and Slack |
| Multimodal | First-class support for text, images, voice, and files — recognition, generation, and delivery |
| Models | Claude, GPT, Gemini, DeepSeek, Qwen, GLM, Kimi, MiniMax, Doubao, and more — swap providers from the Web console with one click |
| Deploy | One-line installer or desktop client, unified Web console, multiple deployment modes (local, Docker, server) |
🏗️ Architecture
CowAgent is a complete Agent Harness: messages flow in through Channels; the Agent Core plans and reasons over memory, knowledge, and the available tools and skills; Models generate the response, which is sent back through the originating channel. Every layer is decoupled and independently extensible.
Read more in Architecture.
🚀 Quick Start
A one-line installer takes care of dependencies, configuration, and startup:
Linux / macOS:
bash <(curl -fsSL https://cdn.link-ai.tech/code/cow/run.sh)
Windows (PowerShell):
irm https://cdn.link-ai.tech/code/cow/run.ps1 | iex
Docker:
curl -O https://cdn.link-ai.tech/code/cow/docker-compose.yml
docker compose up -d
Once started, open http://localhost:9899 to access the Web console — your one-stop hub to chat with the Agent, configure models, connect channels, and install skills.
Deploying on a server? Set web_host to 0.0.0.0 in config.json to make the console reachable from outside, and set web_password to protect it. Don't forget to open port 9899 in your firewall or security group.
📖 Detailed guides: Quick Start · Install from Source · Upgrade
After installation, manage the service with the cow CLI:
cow start | stop | restart # service control
cow status | logs # status and logs
cow update # pull latest code and restart
cow skill install <name> # install a skill
cow install-browser # install browser automation
💻 Desktop client: download the CowAgent Desktop client (macOS / Windows) — the backend is bundled, ready to use out of the box.
☁️ Prefer not to deploy? Open the cloud console to create a dedicated instance with built-in models, online 24/7.
👥 Multi-Agent Team
Create a team of Agents, each with its own memory, capabilities, knowledge, and workspace. Each can focus on its own domain, or collaborate within a shared conversation to tackle complex tasks together. Multi-Agent teams are available on the Web, the desktop client, and IM channel integrations.
See Agent Team for details.
🤖 Models
CowAgent supports all mainstream LLM providers. Chat, vision, image generation, ASR/TTS, and embeddings can each be routed to a different vendor. Providers are configured directly in the Web console — no manual file editing required.
This is the beginning of the README. Read the rest at the original. Read the full README ↗
