CowAgent

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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, 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  ·  ☁️ Try Online

🌟 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) |

🏗️ 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  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](https://docs.cowagent.ai/guide/quick-start) · [Install from Source](https://docs.cowagent.ai/guide/manual-install) · [Upgrade](https://docs.cowagent.ai/guide/upgrade)

After installation, manage the service with the [cow CLI](https://docs.cowagent.ai/cli/index):

```bash
cow start | stop | restart        # service control
cow status | logs                  # status and logs
cow update                         # pull latest code and restart
cow skill install            # 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-fable-5 | ✅ | ✅ | | | | | | OpenAI | gpt-5.5, o-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-k2.7-code | ✅ | ✅ | | | | | | MiniMax | MiniMax-M3 | ✅ | ✅ | ✅ | | ✅ | | | 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.

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 · Three-tier architecture + Deep Dream

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 Hub — open skill marketplace: browse, search, install in one click
• GitHub / ClawHub / URL and more — install skills from any source
• Conversational authoring — generate custom skills through dialogue with skill-creator; turn any workflow or third-party API into a reusable skill

/skill list                   # list installed skills
/skill search         # search the marketplace
/skill install           # one-click install

Learn more: Skills overview · Creating Skills.

🏷 Changelog

> 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).

> 2026.05.22: v2.0.9 — Model management, MCP protocol support, persistent browser sessions, new models (gpt-5.5, gemini-3.5-flash, qwen3.7-max), deployment hardening.

> 2026.05.06: v2.0.8 — Feishu channel overhaul (voice, streaming, QR onboarding), DeepSeek V4 and Baidu Qianfan support, scheduler tool upgrades.

> 2026.04.22: v2.0.7 — Built-in image generation (GPT Image 2, Nano Banana), new models (Kimi K2.6, Claude Opus 4.7, GLM 5.1), memory and knowledge enhancements.

> 2026.04.14: v2.0.6 — Knowledge base, Deep Dream memory distillation, smart context compression, multi-session Web console.

> 2026.04.01: v2.0.5 — Cow CLI, Skill Hub open source, browser tool, WeCom Bot QR onboarding.

> 2026.02.03: v2.0.0 — Major upgrade to a super Agent assistant with multi-step task planning, long-term memory, and the Skills framework.

Full history: Release Notes

🤝 Community & Support

File an issue on GitHub, or scan the QR code below to join our WeChat community:

🔗 Related Projects

• Cow Skill Hub — open skill marketplace for AI Agents; works with CowAgent, OpenClaw, Claude Code, and more
• bot-on-anything — lightweight LLM application framework with integrations for Slack, Telegram, Discord, Gmail, and more
• AgentMesh — open-source multi-agent framework for solving complex problems through team collaboration

🏢 Enterprise Services

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

• 🚀 Zero-deployment hosted runtime — spin up a CowAgent online assistant in under a minute, no server required
• 🧠 Agent infrastructure — unified access to LLMs, knowledge bases, databases, skills, and workflows; plug-and-play building blocks that extend what CowAgent can do
• 🏢 Team & enterprise features — workspaces, role-based access, audit logs, and private deployment for production use cases

For enterprise inquiries: sales@simple-future.tech 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](/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

⚠️ Disclaimer

1. This project is licensed under the [MIT License](/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.

Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: zhayujie
• Source: zhayujie/CowAgent
• License: MIT
• Homepage: https://cowagent.ai

Install and usage instructions live in the source repository linked above.