MEDAS MCP

pip install playwright xlwt httpx
playwright install chromium

uv pip install -e .
playwright install chromium

python server.py

{
  "extensions": {
    "medas": {
      "command": "python",
      "args": ["/path/to/medas_mcp/server.py"],
      "cwd": "/path/to/medas_mcp"
    }
  }
}

{
  "mcpServers": {
    "medas": {
      "command": "python",
      "args": ["/path/to/medas_mcp/server.py"]
    }
  }
}

1. list_topics("fiyat") → [{index:78, label:"Tüketici Fiyat Endeksi"}]
2. get_indicators(78) → {count:12, indicators:[...]}
3. download(78, format="xls") → /tmp/MEDAS_Tüketici_Fiyat_Endeksi_20260820.xls

AI Agent  ⇄  MCP (stdio)  ⇄  server.py  ⇄  medas_client.py
                                            ├─ cache (data/*.json) → instant
                                            └─ Playwright (live=true) → ZK AU protocol

medas_mcp/
├── server.py              # MCP server (3 tools)
├── medas_client.py        # Hybrid client (cache + live Playwright)
├── KNOWHOW.md             # ZK AU protocol traffic notes
├── AGENTS.md              # AI agent instructions
├── README.md              # This file
├── pyproject.toml         # Package metadata
├── .gitignore
└── data/
    ├── topic_mapping.json  # 92 topics with URLs
    ├── topic_gosterge.json # Indicators + cascading branches
    └── medas_unified.json  # Unified dataset