Server data from the Official MCP Registry
Macro data for AI agents: GDP, inflation, unemployment & trade, any country. No API keys.
About
Macro data for AI agents: GDP, inflation, unemployment & trade, any country. No API keys.
Remote endpoints: streamable-http: https://economy.datakoot.com/mcp
Security Report
Valid MCP server (1 strong, 0 medium validity signals). No known CVEs in dependencies. Imported from the Official MCP Registry.
5 tools verified · Open access · No issues found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
Permissions Required
This plugin requests these system permissions. Most are normal for its category.
How to Connect
Remote Plugin
No local installation needed. Your AI client connects to the remote endpoint directly.
Add this to your MCP configuration to connect:
{
"mcpServers": {
"com-datakoot-economy-intel-mcp": {
"url": "https://economy.datakoot.com/mcp"
}
}
}Documentation
View on GitHubFrom the project's GitHub README.
Economy Intel MCP — by Datakoot
Macroeconomic data for AI agents — as MCP tools your agent can call mid-task to ground answers in real GDP, inflation, unemployment and trade figures for any country. No API keys.
Tools
| Tool | What it does | Source |
|---|---|---|
country_indicator | An indicator (GDP, inflation, unemployment, population, ...) for a country over recent years | World Bank |
country_profile | A snapshot of a country's key macro indicators, latest values | World Bank |
compare_countries | Rank one indicator across several countries | World Bank |
us_series | Key US time series: unemployment, CPI, nonfarm payrolls, participation, earnings | US BLS |
list_indicators | Discover every indicator and series this server supports | — |
No API keys required.
Quick start
claude mcp add --transport http economy-intel https://economy.datakoot.com/mcp
Or point any MCP client at https://economy.datakoot.com/mcp.
Grounded, verifiable forecasting
economy-intel is not just data in — it is meant to improve what an agent
concludes. To show that, examples/ has a small, legible agent that
calls this server's us_series mid-task, projects the next macro print against
the market consensus with the arithmetic shown, and submits it to
Headline Arena — a public arena where AI-agent
forecasts are scored against reality and the calibration is checkable by anyone.
The live version runs the loop the arena's maintainer asked for: it wakes on the data-release calendar, discovers the open macro challenges, grounds each one it can in official US series, and posts a forecast with its reasoning — while skipping the challenges it cannot honestly ground (PPI, PMI, the FOMC rate — anything economy-intel does not serve) instead of guessing. Post on signal, not on a clock.
The point is not a clever model. It is that the inputs are official (World Bank, US BLS), the reasoning is transparent, and the record is public. Run the example yourself — no account, no cost:
python3 examples/datakoot_macro_agent.py cpi
Data & attribution
Country data comes from the World Bank Open Data API (CC-BY 4.0); US series come from the US Bureau of Labor Statistics public data API (US public domain). Informational only.
Part of Datakoot — keyless intelligence APIs for AI agents.
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