MEDAS MCP
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@MEDAS MCPTüketici fiyat endeksi göstergelerini listele"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
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-first —
list_topics/get_indicators/downloadall <50ms from cacheBinary 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.$().fire()
Related MCP server: turkiye-veri-mcp
Install
pip install playwright xlwt httpx
playwright install chromiumOr with uv:
uv pip install -e .
playwright install chromiumUsage
As MCP server (stdio)
python server.pyPi integration
Add to ~/.pi/config.json:
{
"extensions": {
"medas": {
"command": "python",
"args": ["/path/to/medas_mcp/server.py"],
"cwd": "/path/to/medas_mcp"
}
}
}Claude Desktop
{
"mcpServers": {
"medas": {
"command": "python",
"args": ["/path/to/medas_mcp/server.py"]
}
}
}Tools
Tool | Description | Speed |
| List 92 TÜİK topics | <50ms (cache) |
| Get indicators + cascading branches | <50ms (cache) |
| Download XLS/CSV report | <50ms cache / ~12s live |
Example flow
1. list_topics("fiyat") → [{index:78, label:"Tüketici Fiyat Endeksi"}]
2. get_indicators(78) → {count:12, indicators:[...]}
3. download(78, format="xls") → /tmp/MEDAS_Tüketici_Fiyat_Endeksi_20260820.xlsArchitecture
AI Agent ⇄ MCP (stdio) ⇄ server.py ⇄ medas_client.py
├─ cache (data/*.json) → instant
└─ Playwright (live=true) → ZK AU protocolCache vs Live
Mode | Source | Speed | Data |
|
| <50ms | Indicator names + mock values |
|
| ~12s | Real MEDAS pivot table |
Files
medas_mcp/
├── server.py # MCP server (3 tools)
├── medas_client.py # Hybrid client (cache + live Playwright)
├── KNOWHOW.md # ZK AU protocol traffic notes
├── AGENTS.md # AI agent instructions
├── README.md # This file
├── pyproject.toml # Package metadata
├── .gitignore
└── data/
├── topic_mapping.json # 92 topics with URLs
├── topic_gosterge.json # Indicators + cascading branches
└── medas_unified.json # Unified datasetZK AU Protocol
POST /medas/zkau;jsessionid=XXXwithdtid+ batchedcmd_n=onSelect/onClickWidget IDs change every session — discovered dynamically via DOM
Cascading:
zk.Widget.$('#selectId').fire('onSelect', {items:[itemId], reference:itemId})
License
MIT
This server cannot be deployed
Maintenance
Related MCP Connectors
Macroeconomic and other official data from 170+ publishers, resolved from natural language with provenance.
Search and query 1,500+ OECD statistical datasets via SDMX. Keyless.
Macro indicators from World Bank, FRED, IMF, and OECD via unified query surface.
Query 29,500+ World Bank development indicators for 200+ countries across 60+ years.
Related MCP Servers
- FlicenseAqualityDmaintenanceEnables querying Turkish economic data (inflation, FX rates, policy rates, etc.) from TCMB EVDS via curated tools, preventing LLM hallucination.6-
- AlicenseAqualityBmaintenanceProvides 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.161MIT
- AlicenseAqualityAmaintenanceMCP server that unifies official Turkish open data sources into a single interface, letting AI agents query and compare normalized indicators like population, inflation, and GDP through natural language.10MIT
- AlicenseNot gradedqualityBmaintenanceEnables querying Bank of Korea ECOS economic statistics via Open API, including searching tables, retrieving time series data, and accessing key indicators.MIT