@pipeworx/imf

Connect: https://gateway.pipeworx.io/imf/mcp · Install: one-click buttons

Tools: 3

The International Monetary Fund’s macro database. Country-level GDP, inflation, current account, fiscal balance, exchange rates, debt, employment, demographics — across 190+ member countries. The standard cross-country macro source. Free, no auth.

Why this matters for AI agents

For cross-country macro analysis, the IMF’s databases (WEO — World Economic Outlook; IFS — International Financial Statistics; BOP — Balance of Payments) are the canonical source. Where FRED is US-focused, IMF is global and harmonized. Where World Bank focuses on development, IMF focuses on macro/fiscal/financial.

Common flows:

• Country macro snapshot. GDP, inflation, current account for a given country.
• Cross-country comparison. Pull the same indicator across multiple countries to compare.
• Time-series analysis. Historical data for trend analysis.

Used by the trade_country_profile compound and pairs well with Comtrade (trade flows) and BLS (US labor).

Auth

None. IMF Data API is fully public, free.

Major databases

Common pitfalls

• Country code variants. IMF uses ISO 3-letter codes (USA, GBR, DEU). Comtrade uses 3-digit numeric. Census uses 2-letter. Cross-source linking needs translation.
• WEO publishes twice yearly. April and October. Forecasts can shift dramatically between releases — always cite the vintage (e.g., “WEO October 2024”).
• Exchange-rate definitions vary. Period average vs. end-of-period vs. PPP vs. real effective. IMF data has all four; specify which.
• Coverage gaps. Small economies and politically isolated countries (North Korea, Venezuela, Eritrea) have spotty data. The IMF API returns nulls; don’t treat null as zero.
• Real vs. nominal. Default GDP is nominal in current-USD. For comparisons over time or across rapid-inflation economies, you usually want real (inflation-adjusted, in constant prices) or PPP-adjusted.
• Lag. Annual data published with 6–18 month lag depending on country reporting. Quarterly data faster, ~2–3 month lag for major economies.

Tools

• get_datasets — List or search the IMF’s datasets — CPI, WEO (World Economic Outlook), BOP (Balance of Payments), IMTS (trade in goods), GFS (government finance), MFS (monetary and financial), FSI (financial soundnes
• get_data — Fetch an IMF time series. Identify the series by dataset plus a dimensions map of named codes, e.g. get_data({dataset:“CPI”, dimensions:{COUNTRY:“USA”, INDEX_TYPE:“CPI”, COICOP_1999:“_T”, TYPE_OF_TR
• search_indicators — Discover what a dataset accepts: its dimension names in key order, and the codes available for each, filtered by query. Use this before get_data — e.g. search_indicators({dataset:“CPI”, query:“unite