CowAgent

CowAgent is an open-source super AI assistant that proactively plans tasks, controls your computer and external services, creates and runs Skills, and grows alongside you through a personal knowledge base and long-term memory — 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.

🌟 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 | | 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, and Official Accounts | | 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) |

🏗️ 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

🤖 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-4-7 | ✅ | ✅ | | | | | | OpenAI | gpt-5.5, o-series | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | | Gemini | gemini-3.5-flash | ✅ | ✅ | ✅ | | | | | DeepSeek | deepseek-v4-flash / pro | ✅ | | | | | | | Qwen | qwen3.7-max | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | | GLM | glm-5.1, glm-5v-turbo | ✅ | ✅ | | ✅ | | ✅ | | Doubao | doubao-seed-2.0 series | ✅ | ✅ | ✅ | | | ✅ | | Kimi | kimi-k2.6 | ✅ | ✅ | | | | | | MiniMax | MiniMax-M2.7 | ✅ | ✅ | ✅ | | ✅ | | | ERNIE | ernie-5.1 | ✅ | ✅ | | | | | | MiMo | mimo-v2.5 / pro | ✅ | ✅ | | | ✅ | | | LinkAI | One key for 100+ models | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | | Custom | Local models / third-party proxy | ✅ | | | | | |

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) | ✅ | ✅ | ✅ | ✅ | | | WeChat | ✅ | ✅ | ✅ | ✅ | | | Feishu / Lark | ✅ | ✅ | ✅ | ✅ | ✅ | | DingTalk | ✅ | ✅ | ✅ | ✅ | ✅ | | WeCom Bot | ✅ | ✅ | ✅ | ✅ | ✅ | | QQ | ✅ | ✅ | ✅ | | ✅ | | WeCom App | ✅ | ✅ | ✅ | ✅ | | | WeChat Official Account | ✅ | ✅ | | ✅ | |

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.

🧠 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.

🔧 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)