OpenEcon Data

Give your AI agent accurate economic data.
330K indicators from FRED, World Bank, IMF, Eurostat, and 6 more sources — one MCP command away.

Website · Live App · Docs · Contributing

Install (One Line, Then Just Talk)

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

That's it. The script auto-detects Claude Code and Codex, configures everything. Then just ask:

You: "What's the US GDP growth rate?"         → your agent fetches real data from FRED
You: "Compare inflation across G7 countries"   → World Bank data for 7 countries
You: "Bitcoin price last 30 days"              → CoinGecko live data

No special syntax. No "use query_data". Just ask naturally — your agent handles the rest.

claude mcp add --transport sse openecon-data https://data.openecon.ai/mcp --scope user

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

Why Your Agent Needs This

AI agents hallucinate economic data. When you ask an LLM "What is US GDP?", you get a plausible-sounding number that may be outdated or wrong. OpenEcon solves this:

How It Compares

What You Can Ask

"US GDP growth last 10 years"                    → FRED, quarterly chart
"Compare China, India, Brazil GDP 2018-2024"     → World Bank, multi-country comparison
"Inflation rate BRICS countries 2019-2023"        → World Bank, 5 countries auto-expanded
"EUR/USD exchange rate last 24 months"            → ExchangeRate-API, currency pair chart
"US unemployment and CPI together since 2010"     → FRED, dual-axis overlay
"China exports to the US 2020-2024"               → UN Comtrade, bilateral trade flow
"Credit to GDP ratio US, UK, Japan from BIS"      → BIS, financial stability data
"Bitcoin price last year"                         → CoinGecko, crypto chart
"What inflation indicators does FRED have?"       → Indicator discovery, text response

Conversational follow-ups work naturally:

You: "US GDP last 5 years"          → chart with US GDP
You: "add Germany and Japan"         → updates to 3 countries
You: "what about per capita?"        → switches to GDP per capita
You: "show only 2020-2023"           → narrows time range

Quick Start

Use the web app (no setup)

data.openecon.ai/chat — no signup, no install.

Self-host

git clone https://github.com/hanlulong/openecon-data.git
cd openecon-data
cp .env.example .env          # Add your OPENROUTER_API_KEY
pip install -r requirements.txt
npm install
python3 scripts/restart_dev.py
# Backend: http://localhost:3001  |  Frontend: http://localhost:5173

How It Works

  "Compare US and           ┌──────────────┐        ┌────────────────┐
   Japan inflation"    ───▶ │  LLM Parser  │  ───▶  │  LLM Router    │
                            │  (intent,    │        │  (semantic      │
                            │   countries, │        │   routing +     │
                            │   dates)     │        │   330K index)   │
                            └──────────────┘        └───────┬────────┘
                                                            │
                            ┌────────────┐          ┌───────▼────────┐
                            │ Chart +    │  ◀────── │  Fetch from    │
                            │ CSV/JSON/  │          │  best provider │
                            │ DTA/Python │          │  (FRED, WB,    │
                            └────────────┘          │   IMF, ...)    │
                                                    └────────────────┘

1. Parse — An LLM extracts intent, countries, indicators, and date range from plain English
2. Route — Semantic routing picks the best provider and series from 330K+ indicators
3. Fetch — Data retrieved from official APIs with automatic fallback if a source is down
4. Return — Interactive chart, or structured data via MCP for your agent

Features

MCP Server — First-class Model Context Protocol support. Give Claude Code, Codex, or any MCP-compatible agent access to verified economic data.

Natural Language — No API docs, no country codes, no series IDs. Just describe what you want.

330K Indicator Discovery — Full-text search across FRED, World Bank, IMF, Eurostat, BIS, and more. Ask "What trade data does Comtrade have?" and get a browsable list.

Multi-Round Conversations — Follow up naturally: add countries, change time ranges, switch indicators. Context is preserved across turns, so "now add Germany" just works.

Smart Routing — The system understands what you mean, not just what you type. It picks the right provider (FRED for US data, World Bank for global comparisons, Comtrade for trade flows) based on the meaning of your query.

Multi-Country Comparisons — Say "G7", "BRICS", "EU", "ASEAN", "Nordic" or list specific countries. Auto-expands to all members.

Fast — Repeat queries return in ~0.1 seconds. First-time queries take ~4 seconds end-to-end.

Resilient — If one provider is down, the system automatically falls back to the next-best source. No manual retries needed.

Clarifies Ambiguity — When a query could mean multiple things ("inflation" could be CPI, PCE, or GDP deflator), the system asks you to pick rather than guessing wrong.

Multi-Format Export — CSV, JSON, DTA (Stata), and Python code. Every export includes source attribution.

Streaming — Real-time progress via Server-Sent Events.

Self-Hostable — AGPL-3.0 licensed. Add new providers by implementing a single base class.

Performance

Data Sources

10 providers, 330K+ indexed indicators:

Who Is This For?

Architecture

┌─────────────────┐     ┌──────────────────┐     ┌──────────────────────────┐
│  User / Agent   │────▶│  FastAPI Backend  │────▶│  Data Providers          │
│                 │     │                  │     │                          │
│  "US inflation" │     │  LLM Parser      │     │  FRED · World Bank · IMF │
│                 │◀────│  LLM Router      │◀────│  Eurostat · BIS · ...    │
│  Chart + Data   │     │  330K Index      │     │                          │
└─────────────────┘     └──────────────────┘     └──────────────────────────┘
        │                        │
   React Frontend          MCP Endpoint
   (Vite + Recharts)     (SSE Transport)

Stack: Python · FastAPI · React · TypeScript · Vite · Recharts · Redis · OpenRouter

Contributing

Contributions welcome! See the Developer & Contributor Guide.

• Open issues — bug reports and feature requests
• Documentation — full docs index
• Security policy — responsible disclosure

If you find this useful, a star helps others discover the project.

License

AGPL-3.0 — Free to use, modify, and self-host. If you run a modified version as a service, you must share your changes. For commercial licensing, contact us.