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README

CowAgent

Latest release License: MIT Stars Docs

zhayujie%2FCowAgent | Trendshift

[English] | [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, 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 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-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-2.0 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.

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 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 <keyword>        # search the marketplace
/skill install <name>          # 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

Core symbols most depended-on inside this repo

get
called by 1528
config.py
get
called by 903
channel/wechat_kf/wechat_kf_cursor_store.py
conf
called by 701
config.py
get
called by 666
agent/tools/mcp/mcp_client.py
error
called by 597
agent/protocol/result.py
t
called by 208
channel/web/static/js/console.js
get
called by 142
bridge/context.py
fail
called by 128
agent/tools/base_tool.py

Shape

Method 1,967
Function 863
Class 339
Route 1

Languages

Python89%
TypeScript11%

Modules by API surface

channel/web/static/js/console.js302 symbols
channel/web/web_channel.py192 symbols
plugins/cow_cli/cow_cli.py64 symbols
channel/wecom_bot/wecom_bot_channel.py53 symbols
cli/commands/skill.py50 symbols
agent/tools/browser/browser_service.py47 symbols
common/cloud_client.py42 symbols
channel/web/static/axios.min.js41 symbols
skills/image-generation/scripts/generate.py40 symbols
tests/test_evolution.py38 symbols
channel/feishu/feishu_channel.py38 symbols
tests/test_qianfan_provider.py37 symbols

Dependencies from manifests, versioned

PyYAML6.0 · 1×
aiohttp3.8.6 · 1×
chardet5.1.0 · 1×
click8.0 · 1×
croniter2.0.0 · 1×
gTTS2.3.1 · 1×
lark-oapi1.5.5 · 1×
numpy1.21 · 1×
pydub0.25.1 · 1×
python-dotenv1.0.0 · 1×
requests2.28.2 · 1×
tiktoken0.3.2 · 1×

For agents

$ claude mcp add CowAgent \
  -- python -m otcore.mcp_server <graph>

⬇ download graph artifact