# 1. Install
pip install "gwanjong-mcp[all]"

# 2. Configure at least one platform
mkdir -p ~/.gwanjong
cat > ~/.gwanjong/.env << 'EOF'
DEVTO_API_KEY=your_key_here
EOF

# 3. Verify setup
gwanjong-mcp  # starts MCP server (use with Claude Code, Cursor, etc.)

claude mcp add gwanjong-mcp -- gwanjong-mcp
claude
> "Find interesting MCP discussions and leave a helpful comment"

pip install "gwanjong-mcp[all,autonomous]"
gwanjong-daemon --topics "MCP,LLM" --dry-run --max-cycles 1

Traditional MCP (14 tools, 9+ round trips):
LLM → list → LLM → trending → LLM → search → LLM → analyze → LLM → get_post
→ LLM → get_comments → LLM → preview → LLM → write → LLM

gwanjong-mcp (5 tools, 3 round trips):
LLM → scout → LLM → draft → LLM (generates content) → strike → done

scout(topic, platforms)
  │  stores → opportunities
  │  Server internally: fetch trending + search + score + filter
  │  Returns: top N scored opportunities (~200 tokens)
  ▼
draft(opportunity_id)
  │  requires → opportunities
  │  stores → contexts
  │  Server internally: fetch post + comments + analyze tone
  │  Returns: context summary + suggested approach (~300 tokens)
  ▼
  LLM generates content based on context
  ▼
strike(opportunity_id, action, content)
     requires → contexts
     Server internally: write via platform API + record history
     Returns: { url, status }

User: "Find interesting MCP discussions and join in"

[1] scout(topic="MCP server", platforms=["devto", "reddit"])
    → Server scans trending + search across platforms → scores → returns top 3
    {
      "opportunities": [
        {"id": "opp_0", "platform": "devto",
         "title": "Best MCP servers for productivity?",
         "relevance": 0.91, "comments": 42,
         "reason": "Active discussion, directly relevant"}
      ]
    }

[2] draft(opportunity_id="opp_0")
    → Server fetches full post + comment tree + tone
    {
      "title": "Best MCP servers for productivity?",
      "body_summary": "...",
      "top_comments": ["...", "..."],
      "tone": "technical, recommendation-seeking",
      "suggested_approach": "Share genuine experience, no self-promo"
    }
    → LLM crafts a helpful, authentic reply

[3] strike(opportunity_id="opp_0", action="comment", content="...")
    → {"url": "https://dev.to/.../comment/...", "status": "posted"}

User: "Write a post about mcp-pipeline on Dev.to"

[1] scout(topic="MCP token optimization", platforms=["devto"])
    → Find what's trending to inform angle and timing

[2] draft(opportunity_id="opp_0")
    → Gather context on existing coverage

[3] LLM writes an original article about the project

[4] strike(opportunity_id="opp_0", action="post", content="...")
    → {"url": "https://dev.to/sonaiengine/...", "status": "posted"}

# All platforms
pip install "gwanjong-mcp[all]"

# Specific platforms
pip install "gwanjong-mcp[devto]"
pip install "gwanjong-mcp[bluesky]"
pip install "gwanjong-mcp[twitter]"
pip install "gwanjong-mcp[reddit]"

# Development
git clone https://github.com/SonAIengine/gwanjong-mcp.git
cd gwanjong-mcp
pip install -e ".[all,dev]"

# Dev.to — https://dev.to/settings/extensions
DEVTO_API_KEY=

# Bluesky — https://bsky.app/settings → App Passwords
BLUESKY_HANDLE=your.handle.bsky.social
BLUESKY_APP_PASSWORD=

# Twitter/X — https://developer.x.com/en/portal/dashboard
TWITTER_API_KEY=
TWITTER_API_SECRET=
TWITTER_ACCESS_TOKEN=
TWITTER_ACCESS_SECRET=

# Reddit — https://www.reddit.com/prefs/apps
REDDIT_CLIENT_ID=
REDDIT_CLIENT_SECRET=
REDDIT_USERNAME=
REDDIT_PASSWORD=

# Register MCP server
claude mcp add gwanjong-mcp -- gwanjong-mcp

# Use with the gwanjong agent (~/.claude/agents/gwanjong.md)
claude agent gwanjong
> "Find interesting AI agent discussions and leave helpful comments"
> "Write a Dev.to post about mcp-pipeline"

# Queue content instead of posting immediately
gwanjong-daemon --require-approval --max-cycles 1

# Review pending items
gwanjong-approval list
gwanjong-approval show 1

# Approve and execute strike immediately
gwanjong-approval approve 1

# Reject without posting
gwanjong-approval reject 2

gwanjong-dashboard
# open http://localhost:8585

gwanjong-mcp/
├── pyproject.toml
├── run.py                         # Direct execution entry point
└── gwanjong_mcp/
    ├── __init__.py
    ├── __main__.py                # python -m gwanjong_mcp
    ├── server.py                  # PipelineMCP + 5 tools + GwanjongState
    ├── setup.py                   # Platform onboarding (guide/save/test)
    └── pipeline.py                # scout/draft/strike pipeline logic

┌─────────────────────────────────────────────────┐
│  Claude Agent (gwanjong.md)                     │
│  Persona · Content generation · Final judgment  │
└──────────────┬──────────────────────────────────┘
               │ 5 tools
┌──────────────▼──────────────────────────────────┐
│  gwanjong-mcp (this project)                    │
│  scout/draft/strike pipeline logic              │
│                                                 │
│  Dependencies:                                  │
│  ├── mcp-pipeline  — Stateful MCP framework     │
│  ├── devhub        — Multi-platform social API  │
│  └── graph-tool-call — Content search engine    │
└─────────────────────────────────────────────────┘

./.venv/bin/python -m pytest -q                    # Default test suite (integration 제외)
./.venv/bin/python -m pytest -m integration -q    # Playwright/network integration tests
./.venv/bin/python -m mypy gwanjong_mcp/          # Type check
./.venv/bin/python -m ruff check gwanjong_mcp/    # Lint
./.venv/bin/python run.py                         # Local server