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FRED (Federal Reserve)

U.S. economic time series — GDP, inflation, interest rates, and 800k+ indicators.

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status: healthy status status healthy healthy tools: 6 tools tools 6 6 type: api wrapper type type api wrapper api wrapper lifecycle: flagship lifecycle lifecycle flagship flagship Economics

Data source: Federal Reserve Economic Data

MCP Endpoint (Streamable HTTP) https://context.gnist.ai/mcp/fred/
Authentication

All requests require a Gnist-API-Key header (or api_key query parameter).

Free tier: 100 calls/day. Get your API key.

Tools (6)

get_series

Get economic time series observations from FRED.

FRED (Federal Reserve Bank of St. Louis) hosts 800,000+ economic time
series from 100+ sources: BLS, BEA, Census, Federal Reserve, IMF, OECD,
World Bank, and more. This is the primary tool for fetching data when
you already know the series ID.

Common series IDs:
- FEDFUNDS — Federal Funds Rate (monthly, %)
- CPIAUCSL — CPI All Urban Consumers (monthly, index)
- UNRATE — Civilian Unemployment Rate (monthly, %)
- GDP — Gross Domestic Product (quarterly, billions USD)
- DGS10 — 10-Year Treasury Yield (daily, %)
- DGS2 — 2-Year Treasury Yield (daily, %)
- T10Y2Y — 10-Year minus 2-Year Treasury spread (daily, %)
- M2SL — M2 Money Stock (monthly, billions USD)
- MORTGAGE30US — 30-Year Fixed Mortgage Rate (weekly, %)
- DEXUSEU — USD/EUR exchange rate (daily)
- PAYEMS — Total Nonfarm Payrolls (monthly, thousands)

Args:
series_id: FRED series identifier (e.g. "FEDFUNDS", "UNRATE", "GDP").
observation_start: Start date (YYYY-MM-DD). If omitted, fetches from the series start.
observation_end: End date (YYYY-MM-DD). If omitted, fetches to the latest available observation.
frequency: Aggregate to lower frequency. Options: "d" (daily), "w" (weekly), "bw" (biweekly),
"m" (monthly), "q" (quarterly), "sa" (semiannual), "a" (annual).
aggregation_method: How to aggregate when changing frequency. Options: "avg" (default), "sum", "eop".
limit: Maximum observations to return (default 100, max 100000).

Returns:
series_id, title, units, frequency, seasonal_adjustment, last_updated,
observation_count, and observations list of {"date": "YYYY-MM-DD", "value": float}.

ParameterTypeRequiredDescription
series_idstringrequiredFRED series identifier (e.g. "FEDFUNDS", "UNRATE", "GDP").
observation_startanyoptionalStart date (YYYY-MM-DD). If omitted, fetches from the series start.
observation_endanyoptionalEnd date (YYYY-MM-DD). If omitted, fetches to the latest available observation.
frequencyanyoptionalAggregate to lower frequency. Options: "d" (daily), "w" (weekly), "bw" (biweekly), "m" (monthly), "q" (quarterly), "sa" (semiannual), "a" (annual).
aggregation_methodanyoptionalHow to aggregate when changing frequency. Options: "avg" (default), "sum", "eop".
limitintegeroptionalMaximum observations to return (default 100, max 100000). (default: 100)
JSON-RPC Request
{
  "jsonrpc": "2.0",
  "method": "tools/call",
  "id": 1,
  "params": {
    "name": "get_series",
    "arguments": {
      "series_id": "example"
    }
  }
}
search_series

Search FRED for economic time series matching a query.

Searches across series titles, notes, and tags. Returns ranked results
sorted by relevance. Use this when you don't know the series ID — then
use get_series() or get_series_info() with the returned series_id.

Example queries:
- "federal funds rate"
- "consumer price index urban"
- "unemployment rate"
- "GDP quarterly"
- "Norway GDP" (FRED includes international series from IMF/OECD/World Bank)
- "yield curve spread"
- "housing starts"

Args:
query: Search terms to match against FRED series names and notes.
limit: Maximum results to return (default 20, max 1000).

Returns:
count and list of matching series with series_id, title, frequency, units,
seasonal_adjustment, date range, last_updated, popularity, and a truncated notes field.

ParameterTypeRequiredDescription
querystringrequiredSearch terms to match against FRED series names and notes.
limitintegeroptionalMaximum results to return (default 20, max 1000). (default: 20)
JSON-RPC Request
{
  "jsonrpc": "2.0",
  "method": "tools/call",
  "id": 1,
  "params": {
    "name": "search_series",
    "arguments": {
      "query": "example"
    }
  }
}
get_series_info

Get metadata for a FRED series without fetching observations.

Useful for verifying a series ID and understanding its characteristics
before fetching data: units, frequency, date range, and whether it is
seasonally adjusted.

Args:
series_id: FRED series identifier (e.g. "FEDFUNDS", "UNRATE", "GDP").

Returns:
Full metadata: series_id, title, frequency, units, seasonal_adjustment,
observation_start, observation_end, last_updated, popularity, and notes.

ParameterTypeRequiredDescription
series_idstringrequiredFRED series identifier (e.g. "FEDFUNDS", "UNRATE", "GDP").
JSON-RPC Request
{
  "jsonrpc": "2.0",
  "method": "tools/call",
  "id": 1,
  "params": {
    "name": "get_series_info",
    "arguments": {
      "series_id": "example"
    }
  }
}
get_category

Browse FRED's category hierarchy.

FRED organizes its 800,000+ series into a tree of categories covering
domains like Money, Banking & Finance; National Accounts; Prices; Labor
Market; International Data; and more. Use this tool to discover series
by topic area. category_id=0 returns the top-level categories.

Args:
category_id: Integer category ID. Default 0 returns the root categories.
Pass a child category ID to drill down. IDs for common
top-level categories:
- 32991: Money, Banking & Finance
- 10: National Accounts
- 9: Population, Employment, & Labor Markets
- 22: Prices
- 3008: U.S. Regional Data
- 32263: Business Cycles

Returns:
Category name, parent_id, children_count, and list of children each with id, name, parent_id.

ParameterTypeRequiredDescription
category_idintegeroptionalInteger category ID. Default 0 returns the root categories. Pass a child category ID to drill down. IDs for common top-level categories: - 32991: Money, Banking & Finance - 10: National Accounts - ... (default: 0)
JSON-RPC Request
{
  "jsonrpc": "2.0",
  "method": "tools/call",
  "id": 1,
  "params": {
    "name": "get_category",
    "arguments": {}
  }
}
compare_series

Fetch multiple FRED series aligned to a common time axis.

Retrieves all requested series and returns their observations aligned
by date — only dates where all series have a value are included.
Ideal for correlation analysis, charting, and comparing economic indicators.

Example use cases:
- compare_series(["FEDFUNDS", "DGS10", "DGS2"]) — Fed Funds vs. yield curve
- compare_series(["UNRATE", "CPIAUCSL"], frequency="q") — unemployment vs. CPI quarterly
- compare_series(["GDP", "PAYEMS"], observation_start="2020-01-01") — GDP vs. payrolls post-COVID

Args:
series_ids: List of 2–10 FRED series IDs to compare.
observation_start: Start date (YYYY-MM-DD) applied to all series.
observation_end: End date (YYYY-MM-DD) applied to all series.
frequency: Aggregate all series to this frequency before aligning (e.g. "q" for quarterly, "a" for annual).

Returns:
series metadata dict (title, units, frequency per series), aligned_observation_count,
and observations list where each row is {"date": "YYYY-MM-DD", "<series_id>": float, ...}.

ParameterTypeRequiredDescription
series_idslist[string]requiredList of 2–10 FRED series IDs to compare.
observation_startanyoptionalStart date (YYYY-MM-DD) applied to all series.
observation_endanyoptionalEnd date (YYYY-MM-DD) applied to all series.
frequencyanyoptionalAggregate all series to this frequency before aligning (e.g. "q" for quarterly, "a" for annual).
JSON-RPC Request
{
  "jsonrpc": "2.0",
  "method": "tools/call",
  "id": 1,
  "params": {
    "name": "compare_series",
    "arguments": {
      "series_ids": [
        "example"
      ]
    }
  }
}
report_feedback

Report a bug, feature request, or general feedback for this data source.

Use this when something doesn't work as expected, when you'd like
a new feature, or when you have suggestions for improvement.

Args:
feedback: Describe the issue or suggestion.
feedback_type: One of 'bug', 'feature_request', or 'general'.

ParameterTypeRequiredDescription
feedbackstringrequired
feedback_typestringoptional (default: "general")
JSON-RPC Request
{
  "jsonrpc": "2.0",
  "method": "tools/call",
  "id": 1,
  "params": {
    "name": "report_feedback",
    "arguments": {
      "feedback": "example"
    }
  }
}

Quick Start

Shell 
curl -X POST "https://context.gnist.ai/mcp/fred/" \
  -H "Content-Type: application/json" \
  -H "Accept: application/json, text/event-stream" \
  -H "Gnist-API-Key: YOUR_API_KEY" \
  -d '{"jsonrpc": "2.0", "method": "tools/call", "id": 1, "params": {"name": "get_series", "arguments": {"series_id": "example"}}}'
Python 
import httpx

resp = httpx.post(
    "https://context.gnist.ai/mcp/fred/",
    headers={"Gnist-API-Key": "YOUR_API_KEY", "Content-Type": "application/json"},
    json={
  "jsonrpc": "2.0",
  "method": "tools/call",
  "id": 1,
  "params": {
    "name": "get_series",
    "arguments": {
      "series_id": "example"
    }
  }
},
)
print(resp.json())

Related Toolkits (Economics)

Economic Indicators
Economic indicators — unified access to World Bank development data, OECD statistics, Eurostat European data, and BLS la
BLS (Bureau of Labor Statistics)
U.S. labor statistics including employment, CPI, wages, and unemployment data.
DST (Statistics Denmark)
Danish official statistics — population, employment, income, housing, trade, and economic data.
ESCO (Skills & Occupations)
European skills, competences, and occupations classification — 13,890 skills and 3,008 occupations linked to ISCO-08 cod

Resources

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Tool Schemas (JSON)
Full input/output JSON schemas for all tools.
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