# CowAgent — Multichannel AI Assistant with Skills and Memory

> CowAgent ships a long-running assistant with skills, browser tools, memory, and channel integrations for teams deploying one agent across chat and web.

## Install

Save the content below to `.claude/skills/` or append to your `CLAUDE.md`:

## Quick Use

1. Fast path on Linux/macOS:
   ```bash
   bash <(curl -fsSL https://cdn.link-ai.tech/code/cow/run.sh)
   ```
2. Or install from source:
   ```bash
   git clone https://github.com/zhayujie/CowAgent
   cd CowAgent
   pip3 install -r requirements.txt
   pip3 install -e .
   ```
3. Verify:
   - Run `cow start`, then confirm one channel or web console session works before enabling browser automation.

## Intro

CowAgent ships a long-running assistant with skills, browser tools, memory, and channel integrations for teams deploying one agent across chat and web.

- **Best for:** operators who need one assistant across chat channels, web console, and optional browser tooling
- **Works with:** Python 3.7-3.13, CLI management, Playwright browser install, WeChat/Feishu/QQ/web channels, knowledge and memory modules
- **Setup time:** 20-45 minutes

## Practical Notes

- Quant: the README supports Python 3.7 through 3.13, which is broader than many newer agent projects.
- Quant: release notes in the README show frequent 2026 updates, including browser tools, skill hub, memory upgrades, and multiple model additions.

## Why it matters

CowAgent is most useful when you want an already opinionated assistant runtime rather than a bare SDK that still needs channel, memory, and browser layers glued on later.

- The project bundles skills, memory, browser tooling, and multiple messaging channels in one repo instead of leaving every integration to the user.
- The `cow` CLI gives clear operational verbs such as start, stop, restart, status, logs, and update.
- The browser layer is optional via `cow install-browser`, which keeps the first rollout smaller than the full capability set.

## Rollout pattern

- Start with one channel or the web console, not every supported channel at once.
- Delay browser automation until the basic dialog, memory, and model configuration path is stable.
- Use a cost-aware model selection because the README warns that agent mode consumes more tokens than normal chat mode.

## Watchouts

This assistant reaches across local systems and external channels, so model cost controls, channel scoping, and browser permissions should be reviewed before broad deployment.

### FAQ

**Q: Can I skip source installs?**
A: Yes. The README provides one-line run scripts for Linux/macOS and PowerShell on Windows.

**Q: What if I need browser actions?**
A: Install the optional browser layer with `cow install-browser` after the base service is stable.

**Q: Why is model choice important?**
A: The maintainers explicitly note that agent mode can use more tokens than standard chat.

## Source & Thanks

> Source: https://github.com/zhayujie/CowAgent
> License: MIT
> GitHub stars: 44,367 · forks: 10,081

---

<!-- ZH -->

## 快速使用

1. Linux/macOS 快速安装：
   ```bash
   bash <(curl -fsSL https://cdn.link-ai.tech/code/cow/run.sh)
   ```
2. 或从源码安装：
   ```bash
   git clone https://github.com/zhayujie/CowAgent
   cd CowAgent
   pip3 install -r requirements.txt
   pip3 install -e .
   ```
3. 验证：
   - 运行 `cow start`，先确认一个通道或 Web 控制台可用，再打开浏览器自动化。

## 简介

CowAgent 提供长期运行的开源 AI 助手，内置技能、浏览器工具、长期记忆与多通道接入，适合想把一个 Agent 同时部署到聊天、网页和企业沟通场景并长期稳定运营维护落地扩展化的团队。

- **适合谁：** 需要把一个助手同时接入聊天通道、Web 控制台和可选浏览器工具的运营团队
- **可搭配：** Python 3.7-3.13、CLI 管理、Playwright 浏览器安装、微信/飞书/QQ/Web 通道与知识记忆模块
- **准备时间：** 20-45 分钟

## 实战建议

- 量化信息：README 明确支持 Python 3.7 到 3.13，这个跨度比很多新 Agent 项目更宽。
- 量化信息：README 里的 2026 更新记录很密集，覆盖浏览器工具、Skill Hub、记忆增强与新模型接入。 

## 为什么值得收录

如果你更想拿到一套“带观点的完整助手运行时”，而不是再自己拼通道、记忆和浏览器层，CowAgent 会更合适。

- 技能、记忆、浏览器工具和多消息通道都在同一个仓库里，不需要用户自己再找一堆插件拼起来。
- `cow` CLI 提供 start、stop、restart、status、logs、update 等明确运维动作。
- 浏览器层通过 `cow install-browser` 可选安装，首次落地不必一次性打开全部能力。

## 落地路径

- 先只开一个通道或 Web 控制台，不要一次把所有支持通道都上线。
- 在基础对话、记忆和模型配置稳定前，不要急着开启浏览器自动化。
- 模型选择要考虑成本，因为 README 已提醒 Agent 模式的 token 消耗高于普通聊天。 

## 注意事项

它会同时触及本地系统和外部通道，因此成本控制、通道范围和浏览器权限都应先做审查再大规模部署。

### FAQ

**一定要源码安装吗？**
答：不一定。README 提供了 Linux/macOS 一行脚本和 Windows PowerShell 快速入口。

**需要浏览器动作怎么办？**
答：先把基础服务跑稳，再用 `cow install-browser` 安装可选浏览器层。

**为什么模型选择很重要？**
答：维护者已明确说明 Agent 模式会比普通聊天消耗更多 token。

## 来源与感谢

> Source: https://github.com/zhayujie/CowAgent
> License: MIT
> GitHub stars: 44,367 · forks: 10,081


---
Source: https://tokrepo.com/en/workflows/cowagent-multichannel-ai-assistant-with-skills-and-memory
Author: Agent Toolkit