98 MCP tools for verifiable AI: citations, law, KYB, peer review, forecast, media provenance.
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.
We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag — we're steadily working through the catalog.
💡 Paste the JSON block into your client's configuration file under mcpServers, then restart the application.
Korean public-data MCP servers for AI agents — KOSIS Statistics Korea (live), BoK ECOS · NEIS · LOCALDATA (planned).
Built and maintained by Vivory. Backend powered by the Vivory Korea Data Gateway.
Korean public statistics (population, GDP, CPI, employment, trade, etc.) are published by official agencies via Korean-only APIs that require local accounts and return JS-literal responses with mixed taxonomies. This repo packages them as Model Context Protocol servers so any MCP-compatible client (Claude Desktop, Claude Code, etc.) can query Korean data in English with zero setup.
No KOSIS account, no API key, no Korean phone — just install and ask.
This is a monorepo of MCP server packages. Each is independently installable from PyPI.
| Package | Status | Tools | Source |
|---|---|---|---|
vivory-mcp-kosis | Live | 15 | KOSIS — Statistics Korea curated key indicators |
vivory-mcp-korea | Live (KOSIS only) | 15 | Umbrella — adds BoK ECOS, NEIS, LOCALDATA, etc. as v0.2+ |
vivory-mcp-kosis)vivory-mcp-korea) — auto-grows as we add sourcesEdit ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):
Or to use the umbrella (all Korean data):
Restart Claude Desktop. The tools appear in the tool palette.
PyPI release pending — until then use:
Ask Claude (or any MCP client):
"What's Korea's CPI trend over the last 24 months?" "Show me Korean quarterly GDP growth, last 12 quarters." "Search KOSIS for tables related to youth unemployment." "What's the indicator ID for 추계인구?"
Claude picks the right tool automatically.
All packages are thin wrappers — no API keys, no rate limit handling, no parsing logic. They translate MCP tool calls → HTTP GETs against api.vivory.app, where the heavy lifting lives.
Set VIVORY_API_BASE to point at your own backend:
The Vivory backend code is not in this repo (it lives in the private Vivory app monorepo). If you want to run the full stack, you'll need to implement the /api/public-tools/kosis/* endpoints yourself or contact us about licensing.
Every tool response includes an attribution block. When citing or redistributing data, include the attribution_required text.
Issues and PRs welcome. Specifically interested in:
vivory-mcp) — packages here mirror what's published to PyPI🇰🇷 Built in Seoul · 🌐 vivory.app
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