MEDAS MCP
MEDAS MCP(仍在开发中!)
MCP 服务器,用于 TÜİK MEDAS(土耳其统计研究所指标)。
功能
92 个主题 — 涵盖所有 TÜİK 统计类别
400+ 个指标 — 即时缓存,支持实时回退
动态发现 — 0 个硬编码 widget ID,自适应 UI 变化
缓存优先 —
list_topics/get_indicators/download均从缓存读取,<50ms二进制 XLS — xlwt CDFV2 Excel 输出(与 MEDAS pivot.xls 格式相同)
智能级联 — 自动选择必填细分(COICOP、SITC 等)
ZK Widget API — 通过
zk.Widget.$().fire()实现稳健的细分处理
Related MCP server: evds-mcp-server
安装
pip install playwright xlwt httpx
playwright install chromium或者使用 uv:
uv pip install -e .
playwright install chromium用法
作为 MCP 服务器(stdio)
python server.pyPi 集成
添加到 ~/.pi/config.json:
{
"extensions": {
"medas": {
"command": "python",
"args": ["/path/to/medas_mcp/server.py"],
"cwd": "/path/to/medas_mcp"
}
}
}Claude Desktop
{
"mcpServers": {
"medas": {
"command": "python",
"args": ["/path/to/medas_mcp/server.py"]
}
}
}工具
工具 | 描述 | 速度 |
| 列出 92 个 TÜİK 主题 | <50ms(缓存) |
| 获取指标及级联分支 | <50ms(缓存) |
| 下载 XLS/CSV 报告 | <50ms 缓存 / ~12s 实时 |
示例流程
1. list_topics("fiyat") → [{index:78, label:"Tüketici Fiyat Endeksi"}]
2. get_indicators(78) → {count:12, indicators:[...]}
3. download(78, format="xls") → /tmp/MEDAS_Tüketici_Fiyat_Endeksi_20260820.xls架构
AI Agent ⇄ MCP (stdio) ⇄ server.py ⇄ medas_client.py
├─ cache (data/*.json) → instant
└─ Playwright (live=true) → ZK AU protocol缓存与实时
模式 | 来源 | 速度 | 数据 |
|
| <50ms | 指标名称 + 模拟值 |
|
| ~12s | 真实 MEDAS 透视表 |
文件
medas_mcp/
├── server.py # MCP server (3 tools)
├── medas_client.py # Hybrid client (cache + live Playwright)
├── KNOWHOW.md # ZK AU protocol traffic notes
├── AGENTS.md # AI agent instructions
├── README.md # This file
├── pyproject.toml # Package metadata
├── .gitignore
└── data/
├── topic_mapping.json # 92 topics with URLs
├── topic_gosterge.json # Indicators + cascading branches
└── medas_unified.json # Unified datasetZK AU 协议
POST /medas/zkau;jsessionid=XXX,带有dtid和批量的cmd_n=onSelect/onClickWidget ID 每次会话都会变化——通过 DOM 动态发现
级联:
zk.Widget.$('#selectId').fire('onSelect', {items:[itemId], reference:itemId})
许可证
MIT
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