Fred MCP server

FRED — Federal Reserve Economic Data

The St. Louis Fed's data warehouse: 800,000+ economic time series spanning interest rates, inflation, employment, GDP, money supply, exchange rates, and metro-level indicators. The most authoritative, continuously updated source for US macro and monetary data — used by economists, policymakers, and journalists.

Part of Pipeworx — an MCP gateway connecting AI agents to 1679+ live data sources.

Why this matters for AI agents

Most "what is the current X" macro questions resolve to a FRED series. An agent that knows the series ID can answer with the actual current value, not a training-data snapshot. Common ones:

• 30-year mortgage rate → MORTGAGE30US
• Federal funds rate → DFF
• CPI (all items) → CPIAUCSL
• Unemployment rate → UNRATE
• 10-year treasury yield → DGS10
• Housing starts → HOUST
• Case-Shiller home price index → CSUSHPISA

If your agent is answering a question about US macroeconomic state, the right pattern is fredsearch (find the right series) → fredseriesinfo (confirm units and frequency) → fredget_series (get the values).

Auth

FRED requires an API key. It's free at https://fred.stlouisfed.org/docs/api/api_key.html — takes 30 seconds, no payment, no rate-limit terror.

Pass via _apiKey per call:

fred_get_series({
  series_id: "MORTGAGE30US",
  _apiKey: "your-fred-api-key"
})

Or subscribe to the Housing Vertical which manages the key for you.

Update cadence

Pipeworx caches FRED responses with TTLs matching these cadences — see caching and freshness.

Citable URI

Embed in your output for stable citations:

pipeworx://fred/series/{series_id}
pipeworx://fred/series/{series_id}/observations

Other agents (and resources/read) can resolve these to the current value of the series.

Reading a fredgetseries response

The last two rows are the one to know about. FRED's observations endpoint echoes observationstart/observationend back as it received them, and substitutes 1600-01-01 / 9999-12-31 when the caller sets neither — so this pack used to report that US GDP ran from 1600 through 9999. Those names now carry the coverage from the series metadata, matching what fredseriesinfo and fred_search already mean by them.

Common pitfalls

• Vintages: FRED preserves historical "vintages" (data as it was reported at time T). Default tool calls get the latest revised series. Pass realtimestart and realtimeend for as-of queries.
• Frequency aggregation: frequency parameter coerces to a different cadence (e.g., daily → monthly average). Default is the series' native frequency.
• Units transformation: units parameter computes derived series at request time (pch for percent change, pca for compound annual rate, etc.). Don't compute these client-side; let FRED do it.
• Series renamed: occasionally the Fed deprecates a series and creates a successor. Old IDs return errors. fred_search is the recovery path.

Quick Start

Shortened. The full README is on GitHub.