agentcrew-mcn 0.2.1

AI MCN 自动推广工具 — 多Agent内容营销自动化，支持掘金/知乎/Dev.to

AgentCrew MCN 🤖

Your AI marketing team. Works 24/7. Never asks for a raise.

📖 中文文档 | English

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What is AgentCrew?

AgentCrew MCN is an open-source multi-agent content marketing automation tool. A team of AI "employees" handles the entire pipeline — from content creation to cross-platform distribution.

• Writer Agent — Copywriter: generates technical articles, social posts, and threads
• Publisher Agent — Operations: publishes to Juejin, Zhihu, Dev.to, and more
• Analyst Agent — Data Analyst: tracks performance and optimizes strategy

Features

• 🧠 Multi-Agent Architecture — Each "employee" operates independently; pluggable design
• 🔧 Skills + Tools System — Atomic operations composed into high-level capabilities
• 📚 RAG Knowledge Base — Retrieval-augmented generation from historical content
• 🎯 Cross-Platform Publishing — Juejin, Zhihu, Dev.to with extensible adapters
• ⏰ Smart Scheduling — Time-based publishing with random jitter to avoid detection
• 🔮 MCP-Ready — Architecture reserved for MCP protocol (v2 roadmap)
• 📊 Dashboard — Web panel for post analytics and agent status
• 🔁 Dogfooding — The project promotes itself

Quick Start

Option 1: pip install (recommended)

# 1. Install
pip install agentcrew-mcn

# 2. Initialize config
agentcrew-mcn init

# 3. Edit .env with your API keys
#    DEEPSEEK_API_KEY=sk-...

# 4. Start using
agentcrew-mcn write generate --topic "Python async programming" --style technical
agentcrew-mcn publish post --file article.md --platform juejin --dry-run

💡 agent-crew is also available as an alias for agentcrew-mcn.

Option 2: From source

# 1. Clone
git clone https://github.com/super-rick/agentcrew-mcn.git
cd agentcrew-mcn

# 2. Install dependencies
pip install -r requirements.txt

# 3. Initialize
python -m cli.main init

# 4. Edit .env with your API keys

Configuration

agentcrew-mcn init creates a config template. Key settings:

# config.yaml
llm:
  api_key: ${DEEPSEEK_API_KEY}  # Reads from .env
  model: deepseek-chat

platforms:
  juejin:
    cookie: ${JUEJIN_COOKIE}    # Export cookie from browser
  devto:
    api_key: ${DEVTO_API_KEY}   # https://dev.to/settings/extensions

Usage

# Generate a technical article
agentcrew-mcn write generate --topic "Python async programming" --style technical

# Preview mode (no LLM call, inspect parameters)
agentcrew-mcn write generate --topic "Python async" --dry-run

# Publish to Juejin
agentcrew-mcn publish post --file article.md --platform juejin

# Scheduled publishing (every 6 hours)
agentcrew-mcn schedule start --topic-file topics.txt --platform juejin --interval 6

# RAG knowledge base
agentcrew-mcn rag ingest --file article.md --source "my_blog"
agentcrew-mcn rag search --query "AI Agent architecture"

Architecture

┌─────────────────────────────────────────────────────┐
│                   Orchestrator                       │
│           Task dispatch / Scheduler / Config          │
└──┬──────────┬──────────────┬────────────────────────┘
   │          │              │
┌──▼──────┐ ┌▼────────┐ ┌──▼────────┐
│ Writer  │ │Publisher│ │  Analyst  │
│ Agent   │ │Agent    │ │  Agent    │
│         │ │         │ │           │
│ Skills: │ │ Skills: │ │ Skills:   │
│ trending│ │ schedule│ │ report    │
│ tech    │ │ multi   │ │ recommend │
│ thread  │ │ batch   │ │           │
│         │ │         │ │           │
│ Tools:  │ │ Tools:  │ │ Tools:    │
│ search  │ │ devto   │ │ analytics │
│ rag     │ │ juejin  │ │ compare   │
│ compose │ │ zhihu   │ │ report    │
└─────────┘ └─────────┘ └───────────┘

Tech Stack

Component	Technology
Language	Python 3.10+
CLI	Click + Rich
LLM	DeepSeek API (OpenAI-compatible)
Vector DB	ChromaDB
Automation	Playwright
Dashboard	Streamlit + Plotly

Roadmap

See ROADMAP.md for details.

• v0.1 ✅ Writer + Publisher + CLI + Juejin/Zhihu + Dashboard + Analyst
• v0.2 📝 Dev.to adapter + Zhihu MD fix + Bilingual README
• v0.3 🔜 Skill Store + more platforms + A/B testing
• v1.0 🔮 MCP protocol + community plugins

License

MIT