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 1476+ 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 fred_search (find the right series) → fred_series_info (confirm units and frequency) → fred_get_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

Series class	Update frequency
Daily series (rates, exchange rates)	Daily, ~1 business day lag
Weekly (mortgage rates)	Weekly, Thursday
Monthly (CPI, unemployment, retail sales)	Monthly, ~2-3 weeks after month end
Quarterly (GDP)	Quarterly, ~1 month after quarter end

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.

Common pitfalls

Vintages: FRED preserves historical "vintages" (data as it was reported at time T). Default tool calls get the latest revised series. Pass realtime_start and realtime_end 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

Add to your MCP client (Claude Desktop, Cursor, Windsurf, etc.):

{
  "mcpServers": {
    "fred": {
      "url": "https://gateway.pipeworx.io/fred/mcp"
    }
  }
}

What this endpoint actually serves

tools/list at https://gateway.pipeworx.io/fred/mcp returns the tools in the table above plus the shared Pipeworx meta-tools — ask_pipeworx, discover_tools, search_within, remember/recall and the rest of the gateway-wide set. So the tool count you see is larger than this table: a single-pack endpoint currently lists roughly 30 shared tools alongside the pack's own. The connection's initialize response states its exact scope, and is the authoritative answer for a given day.

This is deliberate, not multiplexing by accident. The meta-tools are what let a scoped connection answer a question this pack does not cover — via ask_pipeworx, which routes across the whole catalog — without you adding a second MCP server. There is currently no way to mount a pack endpoint without them; if the extra schemas cost you more context than the routing is worth, connect to the full gateway once rather than to several pack endpoints.

Or connect to the full Pipeworx gateway to get every pack's tools listed directly, instead of just this one's:

{
  "mcpServers": {
    "pipeworx": {
      "url": "https://gateway.pipeworx.io/mcp"
    }
  }
}

Both URLs reach the same gateway and the same 1476+ data sources. The only difference is which pack's tools are listed directly; ask_pipeworx reaches all of them from either one.

Using with ask_pipeworx

Instead of calling tools directly, you can ask questions in plain English — this works on the pack endpoint above as well as on the full gateway:

ask_pipeworx({ question: "your question about Fred data" })

The gateway picks the right tool and fills the arguments automatically.

License

MIT

Fred