
Connects Claude to the Federal Reserve Economic Data API from the St. Louis Fed, giving you programmatic access to thousands of U.S. economic time series. Part of the Pipeworx gateway, which routes requests to 673+ data sources. You can call tools directly or use the ask_pipeworx interface to query in plain English and let the gateway handle tool selection and argument mapping. Useful when you need inflation rates, unemployment figures, GDP data, or any other Fed tracked metric without leaving your AI workflow. Runs over streamable HTTP, so no local setup required.
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.
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:
MORTGAGE30USDFFCPIAUCSLUNRATEDGS10HOUSTCSUSHPISAIf 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).
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.
| 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.
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.
realtime_start and realtime_end for as-of queries.frequency parameter coerces to a different cadence (e.g., daily → monthly average). Default is the series' native frequency.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.fred_search is the recovery path.Add to your MCP client (Claude Desktop, Cursor, Windsurf, etc.):
{
"mcpServers": {
"fred": {
"url": "https://gateway.pipeworx.io/fred/mcp"
}
}
}
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.
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.
MIT