Skip to main content
Glama
bluedragonDC

MEDAS MCP

by bluedragonDC

MEDAS MCP (Still in development!)

MCP server for TÜİK MEDAS (Turkish Statistical Institute indicators).

Features

  • 92 topics — all TÜİK statistical categories

  • 400+ indicators — cached instantly, live fallback available

  • Dynamic discovery — 0 hardcoded widget IDs, adaptive to UI changes

  • Cache-firstlist_topics/get_indicators/download all <50ms from cache

  • Binary XLS — xlwt CDFV2 Excel output (same format as MEDAS pivot.xls)

  • Smart cascading — auto-selects mandatory breakdowns (COICOP, SITC, etc.)

  • ZK Widget API — robust kırılım handling via zk.Widget.$().fire()

Related MCP server: evds-mcp-server

Install

pip install playwright xlwt httpx
playwright install chromium

Or with uv:

uv pip install -e .
playwright install chromium

Usage

As MCP server (stdio)

python server.py

Pi integration

Add to ~/.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"]
    }
  }
}

Tools

Tool

Description

Speed

list_topics(search?)

List 92 TÜİK topics

<50ms (cache)

get_indicators(topic_index)

Get indicators + cascading branches

<50ms (cache)

download(topic_index, indicators?, format?, save_path?, live?)

Download XLS/CSV report

<50ms cache / ~12s live

Example flow

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

Architecture

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

Cache vs Live

Mode

Source

Speed

Data

live=false (default)

data/*.json cache

<50ms

Indicator names + mock values

live=true

POST /medas/zkauGET /pivot.xls

~12s

Real MEDAS pivot table

Files

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

ZK AU Protocol

  • POST /medas/zkau;jsessionid=XXX with dtid + batched cmd_n=onSelect/onClick

  • Widget IDs change every session — discovered dynamically via DOM

  • Cascading: zk.Widget.$('#selectId').fire('onSelect', {items:[itemId], reference:itemId})

License

MIT

Related MCP Connectors

Related MCP Servers

  • A
    license
    A
    quality
    C
    maintenance
    Enables users to search and access Turkish public procurement data from EKAP v2 portal. Provides comprehensive tender search, detailed tender information, announcements, and authority/classification code lookups through natural language interactions.
    12
    100
    MIT
  • F
    license
    A
    quality
    C
    maintenance
    Enables querying Turkish economic data (inflation, FX rates, policy rates, etc.) from TCMB EVDS via curated tools, preventing LLM hallucination.
    6
    -
  • A
    license
    Not graded
    quality
    C
    maintenance
    Enables querying Kosovo Agency of Statistics (ASKdata) data through PxWeb. Supports navigating subjects, exploring table metadata, and fetching data via natural language or direct tool calls.
    2 npm
    MIT
  • A
    license
    A
    quality
    B
    maintenance
    Provides unified access to Turkish official data from TÜİK (statistics via SDMX) and TCMB EVDS (financial series), enabling search, query, and tidy CSV export with full frequency, aggregation, and formula support.
    16
    1
    MIT