CowAgent README

The project's README from github.com/zhayujie/CowAgent. As one markdown file: README.md.

CowAgent

Latest release License: MIT Stars Docs WeChat Group Discord

zhayujie%2FCowAgent | Trendshift

[English] | [中文] | [繁體中文] | [日本語]

CowAgent 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, forms multi-agent teams, 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.

🌐 Website  ·  📖 Docs  ·  🚀 Quick Start  ·  🧩 Skill Hub  ·  💻 Download  ·  ☁️ Try Online


🎬 Demo

Your browser can't play this video. Watch the demo on our website →


🌟 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, unified Web console, multiple deployment modes (local, Docker, server)

🏗️ Architecture

CowAgent 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.


👥 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.

CowAgent Multi-Agent Team

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.

Provider Featured Models Chat Vision Image Gen ASR TTS Embedding
DeepSeek deepseek-flash (V4.1) / pro ✅ ✅
Claude claude-opus-5 / fable-5.1 ✅ ✅
OpenAI gpt-6-astra / gpt-5.6 series ✅ ✅ ✅ ✅ ✅ ✅
Gemini gemini-3.8-flash ✅ ✅ ✅
MiniMax MiniMax-M3 ✅ ✅ ✅ ✅
GLM glm-5.3-flash, glm-5v-turbo ✅ ✅ ✅ ✅
Qwen qwen3.8-flash ✅ ✅ ✅ ✅ ✅ ✅
Kimi kimi-k3 ✅ ✅
Doubao doubao-seed-2.1 series ✅ ✅ ✅ ✅
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) ✅ ✅ ✅ ✅
Telegram ✅ ✅ ✅ ✅ ✅
Slack ✅ ✅ ✅ ✅
Discord ✅ ✅ ✅ ✅
WeChat ✅ ✅ ✅ ✅
Feishu / Lark ✅ ✅ ✅ ✅ ✅
DingTalk ✅ ✅ ✅ ✅ ✅
WeCom Bot ✅ ✅ ✅ ✅ ✅
QQ ✅ ✅ ✅ ✅
WeCom App ✅ ✅ ✅ ✅
WeChat Customer Service ✅ ✅ ✅ ✅
WeChat Official Account ✅ ✅ ✅

See the Channels overview for setup details.

CowAgent Web Console

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.

Long-term Memory

Long-term Memory · Three-tier architecture + Deep Dream

Personal Knowledge Base

Knowledge Base · Auto-curated Markdown wiki


🔧 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 servers. A single mcp.json is enough — supports stdio / SSE transports, hot reload, and zero-code integration.

Learn more: Tools overview · MCP integration.

Skills System

/skill list                   # list installed skills
/skill search <keyword>        # search the marketplace
/skill install <name>          # one-click install

Learn more: Skills overview · Creating Skills.


🏷 Changelog

2026.09.10: v2.1.8 — Multi-Agent teams, manual scheduled task creation, context-usage visualization, new models and search providers, workspace file editing.

2026.08.20: v2.1.7 — Multiple workspaces, session-level permission modes, task notifications, desktop improvements, plus new model support.

2026.08.12: v2.1.6 — Sub agents for parallel task delegation, reasoning-effort settings, a pluggable memory vector backend, plus experience and security improvements.

2026.07.29: v2.1.5 — Workspace with file preview, core tool improvements (file search, write-time validation, background commands), context compaction (/compact), one-click prompt optimization, security hardening.

2026.07.20: v2.1.4 — Desktop experience improvements, MCP OAuth authorization, Lark channel enhancements, scheduler improvements and data backup, new models.

2026.07.08: v2.1.3 — Desktop client for macOS / Windows, knowledge base document management, on-demand MCP tool retrieval, Traditional Chinese support, new models.

2026.06.18: v2.1.2 — Web console upgrades (scheduled task management, knowledge base categories, multiple custom model providers), Self-Evolution improvements, new models (kimi-k2.7-code, glm-5.2), security hardening and refinements.

2026.06.09: v2.1.1 — Self-Evolution, Web console upgrades (message management, parallel sessions), cross-platform MCP enhancements with concurrent calls, new models (MiniMax-M3, qwen3.7-plus), Python 3.13 support.

2026.06.01: v2.1.0 — Internationalization, new channels (Telegram, Discord, Slack, WeChat Customer Service), CLI interaction upgrades, streamlined one-line install, MCP Streamable HTTP support, new models (claude-opus-4-8, MiMo).

Full history: Release Notes


🤝 Community & Support

Join our Discord server to ask questions, share skills, and follow development:

Join our Discord

You can also file an issue on GitHub, or scan the QR code below to join our WeChat group:



🏢 Enterprise Services

LinkAI is an all-in-one AI Agent platform for enterprises and developers, offering managed hosting and enterprise-grade support for CowAgent:

For enterprise inquiries: [email protected] or scan the QR code to reach our team on WeChat.


🛠️ Development & Contributing

All kinds of contributions are welcome — new features, bug fixes, performance improvements, docs, or sharing your own skills on the Skill Hub. See CONTRIBUTING.md to get started, then open an Issue to discuss or send a PR directly.

⭐ Star the project to show your support, and Watch → Custom → Releases to get notified of new versions. PRs and Issues are always welcome.

🌟 Contributors

cow contributors


⚠️ Disclaimer

  1. This project is licensed under the MIT License and is intended for technical research and learning. You are responsible for complying with applicable laws and regulations in your jurisdiction; the maintainers assume no liability for any consequences arising from use of this project.
  2. Cost & safety: Agent mode consumes substantially more tokens than regular chat — pick models that balance quality and cost. The Agent has access to your local operating system, so only deploy it in trusted environments.
  3. CowAgent is a pure open-source project and does not participate in, authorize, or issue any cryptocurrency.

📌 Project Renaming Notice

This project was previously named chatgpt-on-wechat and is now officially CowAgent. The old GitHub URL redirects automatically; existing users may optionally run git remote set-url origin https://github.com/zhayujie/CowAgent.git to update the local remote.

CowAgent (zhayujie/CowAgent)

Searching Database…

47.4K ·GitHub
这是什么?CowAgent 是一款开源的个人 AI 助手,也是一个 Agent Harness。它可以规划任务、运行工具和技能、建立记忆和个人知识库,还能组建多智能体团队,并可在网页端和主流即时通讯渠道中使用。
这是可以导入的代码库,还是可以独立运行的应用?这是一款需要你自行部署和运行的独立应用(可通过一行命令安装脚本、Docker 或桌面客户端使用),而不是需要导入到代码中的库。
我该怎么让它跑起来?在 Linux/macOS 上运行一行命令安装脚本,或在 Windows 上运行 PowerShell 脚本(也可以使用 Docker)。安装完成后会打开 Web 控制台,你可以在里面配置模型、渠道和技能。macOS 和 Windows 还提供配套的桌面客户端。
我需要从大模型服务商那里获取 API Key 吗?需要。你至少要接入一家大模型服务商(如 Claude、GPT、Gemini、DeepSeek、Qwen、GLM、Kimi 等),直接在 Web 控制台中完成接入即可,无需手动编辑文件。
部署前有什么需要注意的地方吗?Agent 模式消耗的 token 远多于普通聊天,因此费用会随使用量增长。项目还提醒,只应在可信环境中运行它,因为 Agent 可以直接操作你的本地操作系统。
Agent 能访问我的电脑和数据吗?能。Agent 可以读写文件、执行终端命令并控制本地系统,因此只应部署在你信任的环境中。
它的记忆系统和普通的聊天记录有什么不同?记忆系统采用三层架构(上下文 → 每日 → 核心)。每晚会运行一次“Deep Dream”流程,把零散的记忆提炼成精炼的长期条目和一份叙事日记,同时结合关键词与向量的混合检索。
我该如何为 Agent 添加新技能?你可以从 Skill Hub 技能市场、GitHub 或 ClawHub 一键安装技能,也可以使用 skill-creator,用自然语言描述一个工作流程,就能创建自定义技能。
它可以连接哪些即时通讯平台?它支持接入 Web、WeChat、Feishu/Lark、DingTalk、WeCom、QQ、Telegram、Slack、Discord 和 WeChat Official Accounts,其中大多数可以直接在 Web 控制台中完成接入。
这个项目一直叫 CowAgent 吗?不是。它之前的名字是 chatgpt-on-wechat,现在正式更名为 CowAgent;旧的 GitHub 地址会自动跳转到新仓库。
What are similar projects?Raven, brigade, opensquilla, hermes-agent, ruflo, lobehub, EvoQuant, hive
Creator
zhayujie
Size
21.8 MB
Stars
47.4K
Age
4y
Commits · 90 Days