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openecon-data

by hanlulong·41·Score 45

MCP server providing 330K+ economic indicators from FRED, World Bank, IMF & more for AI agents.

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Overview

OpenEcon Data is an MCP server that connects AI agents to authoritative economic data sources. It allows natural language queries to retrieve verified economic indicators across 10+ data sources including FRED, World Bank, IMF, Eurostat, and others. The system uses LLM parsing to translate natural language queries into structured API calls, then routes to the appropriate data source. It supports multi-round conversations, automatic country grouping (G7, BRICS, etc.), and smart indicator discovery from its 330K+ indexed series.

Try asking AI

After installing, here are 6 things you can ask your AI assistant:

you:Economists and researchers quickly retrieve verified economic data without writing API code
you:AI agents access real-time economic data to reduce hallucinations in financial analysis
you:Journalists fact-check economic claims against official sources in seconds
you:What economic sources are supported?
you:How does the natural language processing work?
you:Can I self-host this service?

When to choose this

Choose OpenEcon when your AI agent needs reliable economic data without hallucination, especially for macroeconomic analysis across multiple countries or when you want natural language queries instead of manual API codes.

When NOT to choose this

Don't choose OpenEcon if you need write access to economic databases, as this is a read-only service; if you're looking for non-economic time series data; or if you require offline access to the data.

Tools this server exposes

12 tools extracted from the README
  • query_economic_data

    Fetch economic data from multiple sources including FRED, World Bank, IMF, and others based on natural language queries.

  • compare_countries

    Compare economic indicators across multiple countries or country groups like G7, BRICS, or EU.

  • fetch_indicator_metadata

    Search and retrieve metadata about available economic indicators from various data providers.

  • get_time_series_data

    Retrieve historical time series data for specific economic indicators with customizable date ranges.

  • analyze_bilateral_trade

    Analyze bilateral trade flows between countries using UN Comtrade data.

  • fetch_financial_stability_data

    Retrieve financial stability indicators from sources like BIS.

  • get_crypto_data

    Fetch cryptocurrency market data and prices from CoinGecko.

  • get_exchange_rates

    Retrieve currency exchange rates and currency pair data.

  • get_development_indicators

    Access global development indicators from World Bank.

  • fetch_imf_data

    Retrieve economic data from International Monetary Fund.

  • analyze_eu_statistics

    Access Eurostat data for EU member states.

  • get_canadian_data

    Fetch Canadian economic statistics from Statistics Canada.

Note: Inferred from natural language examples in the README. While the README mentions MCP server functionality, it doesn't explicitly list tool names. Tool names were constructed based on query types described in the 'What You Can Ask' section a

Comparable tools

fredapipandas-datareaderfred-mcp-server

Installation

Quick Install

curl -fsSL https://raw.githubusercontent.com/hanlulong/openecon-data/main/scripts/install.sh | bash

Claude Desktop Configuration

Add to Claude's config.json:

{
  "mcpServers": {
    "open-econ-data": {
      "command": "curl",
      "args": ["-s", "https://data.openecon.ai/mcp"],
      "env": {}
    }
  }
}

Manual Install

# For Claude Code
claude mcp add --transport sse openecon-data https://data.openecon.ai/mcp --scope user

# For Codex
codex mcp add openecon-data --url https://data.openecon.ai/mcp

Web demo available at: https://data.openecon.ai/chat

FAQ

What economic sources are supported?
OpenEcon Data supports 10+ data sources including FRED (90K+ indicators), World Bank, IMF, Eurostat, UN Comtrade, BIS, Statistics Canada, OECD, ExchangeRate-API, and CoinGecko.
How does the natural language processing work?
The system uses an LLM parser to extract intent, countries, indicators, and date ranges from plain English queries. It then uses semantic routing to match queries to the appropriate data source from its 330K+ indexed indicators.
Can I self-host this service?
Yes, the project is AGPL-3.0 licensed and can be self-hosted. You'll need an OpenRouter API key and optionally API keys for specific data sources like FRED or CoinGecko.

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Last updated · Auto-generated from public README + GitHub signals.