CowAgent
Open-source super AI assistant & Agent Harness. Plans tasks, runs tools and skills, self-evolves with memory and knowledge. Multi-agent, multi-model, multi-channel. Lightweight, extensible, one-line install.
Install / Use
npx skills add zhayujie/CowAgentInstalls into whichever agent you are using.
CLAUDE.md
Claude Code project instructions
Quality Score
Category
AI & Machine LearningSupported Platforms
Skill content
View source on GitHubCowAgent is an open-source super AI assistant that proactively plans tasks, controls your computer and external services, creates and runs Skills, builds a personal knowledge base and long-term memory, and grows alongside you through self-evolution — a reference implementation of Agent Harness engineering.
CowAgent is lightweight, easy to deploy, and built to extend. Plug in any major LLM provider and run it 24/7 on a personal computer or server, across the web and all major IM platforms.
<p align="center"> <a href="https://cowagent.ai/">🌐 Website</a> · <a href="https://docs.cowagent.ai/intro/index">📖 Docs</a> · <a href="https://docs.cowagent.ai/guide/quick-start">🚀 Quick Start</a> · <a href="https://skills.cowagent.ai/">🧩 Skill Hub</a> · <a href="https://cowagent.ai/download/">💻 Download</a> · <a href="https://link-ai.tech/cowagent/create">☁️ Try Online</a> </p> <br/>🎬 Demo
<p align="center"> <video src="https://github.com/user-attachments/assets/8625a19f-615c-4343-8be8-3707ce4d4d4e" controls muted playsinline width="720"> Your browser can't play this video. <a href="https://cowagent.ai/">Watch the demo on our website →</a> </video> </p> <br/>🌟 Highlights
| Capability | Description | | :--- | :--- | | Planning | Decomposes complex tasks and executes them step by step, looping over tools until the goal is reached | | 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, unified Web console, multiple deployment modes (local, Docker, server) |
<br/>🏗️ Architecture
<img src="https://cdn.jsdelivr.net/gh/zhayujie/cowagent-assets@main/architecture/en/architecture.png" alt="CowAgent Architecture" width="750"/>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.
<br/>🚀 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_hostto0.0.0.0inconfig.jsonto make the console reachable from outside, and setweb_passwordto protect it. Don't forget to open port9899in 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
<br/>💻 Desktop client: download the CowAgent Desktop client (macOS / Windows) — the backend is bundled, ready to use out of the box.
🤖 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.
| Provider | Featured Models | Chat | Vision | Image Gen | ASR | TTS | Embedding | | --- | --- | :-: | :-: | :-: | :-: | :-: | :-: | | Claude | claude-opus-5 / sonnet-5 | ✅ | ✅ | | | | | | OpenAI | gpt-5.6 series | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | | Gemini | gemini-3.5-flash | ✅ | ✅ | ✅ | | | | | DeepSeek | deepseek-v4-flash / pro | ✅ | | | | | | | Qwen | qwen3.7-plus | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | | GLM | glm-5.2, glm-5v-turbo | ✅ | ✅ | | ✅ | | ✅ | | Doubao | doubao-seed-2.1 series | ✅ | ✅ | ✅ | | | ✅ | | Kimi | kimi-k3 | ✅ | ✅ | | | | | | MiniMax | MiniMax-M3 | ✅ | ✅ | ✅ | | ✅ | | | ERNIE | ernie-5.1 | ✅ | ✅ | | | | | | MiMo | mimo-v2.5 / pro | ✅ | ✅ | | | ✅ | | | LinkAI | One key for 100+ models | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | | Custom | Local models / third-party proxy | ✅ | | | | | |
<br/>For details on each provider, see the Models overview.
💬 Channels
A single Agent instance can serve multiple channels in parallel. Most channels can be onboarded right from the Web console.
| Channel | Text | Image | File | Voice | Group | | --- | :-: | :-: | :-: | :-: | :-: | | Web Console (default) | ✅ | ✅ | ✅ | ✅ | | | Telegram | ✅ | ✅ | ✅ | ✅ | ✅ | | Slack | ✅ | ✅ | ✅ | | ✅ | | Discord | ✅ | ✅ | ✅ | | ✅ | | WeChat | ✅ | ✅ | ✅ | ✅ | | | Feishu / Lark | ✅ | ✅ | ✅ | ✅ | ✅ | | DingTalk | ✅ | ✅ | ✅ | ✅ | ✅ | | WeCom Bot | ✅ | ✅ | ✅ | ✅ | ✅ | | QQ | ✅ | ✅ | ✅ | | ✅ | | WeCom App | ✅ | ✅ | ✅ | ✅ | | | WeChat Customer Service | ✅ | ✅ | ✅ | ✅ | | | WeChat Official Account | ✅ | ✅ | | ✅ | |
<img src="https://cdn.jsdelivr.net/gh/zhayujie/cowagent-assets@main/screenshots/en/web-console-chat.png" alt="CowAgent Web Console" width="800"/>See the Channels overview for setup details.
The Web console is the default channel and the unified entry point to configure models, channels, skills, memory, and more.
<br/>🧠 Memory & Knowledge Base
Long-term memory uses a three-tier architecture: conversation context (short-term) → daily memory (mid-term) → MEMORY.md (long-term). A nightly Deep Dream pass distills scattered memories into refined long-term entries and a narrative journal. See Long-term Memory · Deep Dream.
Personal knowledge base complements the time-ordered memory by organizing structured knowledge by topic. The Agent automatically curates valuable information from conversations, maintains cross-references and indexes, and the Web console offers an interactive knowledge-graph view. See Personal Knowledge Base.
<table> <tr> <td width="50%"> <img src="https://cdn.jsdelivr.net/gh/zhayujie/cowagent-assets@main/screenshots/en/web-console-memory.png" alt="Long-term Memory" /> <p align="center"><em>Long-term Memory · Three-tier architecture + Deep Dream</em></p> </td> <td width="50%"> <img src="https://cdn.jsdelivr.net/gh/zhayujie/cowagent-assets@main/screenshots/en/web-console-knowledge.png" alt="Personal Knowledge Base" /> <p align="center"><em>Knowledge Base · Auto-curated Markdown wiki</em></p> </td> </tr> </table> <br/>🔧 Tools & Skills
Tools are atomic capabilities the Agent uses to interact with system resources. Skills are higher-level workflows defined by a manifest file that compose multiple tools to accomplish complex tasks.
Tool System
Built-in tools cover file I/O (read / write / edit / ls), terminal (bash), file sending (send), memory retrieval (memory), environment variables (env_config), web fetching (web_fetch), scheduling (scheduler), web search (web_search), vision (vision), and browser automation (browser).
MCP protocol integrates the open ecosystem of [Model Context Protocol]
Truncated for display — read the full file on GitHub.
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