AI Agent Data Analysis: Query FRED, Census, and BLS in One Conversation

The US government publishes some of the best economic data in the world. The problem is getting to it. Three major sources cover most of what analysts, journalists, and researchers need: FRED for financial and macroeconomic indicators, the Census Bureau for demographics and population, and BLS for labor market data. Each has its own API format, its own identifier system, and its own quirks. Most people end up clicking through web portals instead of writing code.

AI agent data analysis changes the workflow. Instead of memorizing that the unemployment rate lives in FRED series UNRATE or that Census table B01003 holds total population, you describe what you want in plain English. The agent figures out the right source, the right identifiers, and the right parameters.

What Each Source Offers

FRED (Federal Reserve Economic Data) contains over 800,000 time series. GDP, interest rates, inflation measures, housing starts, exchange rates, commodity prices. The St. Louis Fed maintains it, and it pulls in data from dozens of other agencies. The challenge: you need to know the exact series ID to pull data. CPIAUCSL for consumer prices. DFF for the federal funds rate. GDP for nominal GDP. Nobody remembers all of these.

Census Bureau covers population, housing, income, poverty, health insurance, education, and more. The American Community Survey (ACS) runs every year and produces detailed breakdowns by geography. Want median household income for a specific county? It exists. Finding it means navigating a hierarchy of tables, variables, and geographic codes.

BLS (Bureau of Labor Statistics) tracks employment, wages, productivity, prices, and workplace safety. The monthly jobs report comes from BLS. So does the Consumer Price Index. Their API uses series IDs like LNS14000000 (unemployment rate) or CUUR0000SA0 (CPI for all urban consumers). Not intuitive.

What an Agent Can Do With These

A single conversation can span all three sources. Consider this prompt:

“What’s the current unemployment rate, how has CPI changed over the past 12 months, and what’s the population of Travis County, Texas?”

Without tools, an agent would guess or refuse. With the right tools, it can:

  1. Search FRED for the unemployment rate series, then pull the latest values
  2. Query BLS for CPI data across the past year
  3. Hit the Census ACS for Travis County population estimates

The results come back structured and ready to compare. No tab-switching, no manual downloads, no CSV wrangling.

More useful prompts:

“Compare the federal funds rate to the 10-year Treasury yield over the past 5 years.”

“Pull median household income for the 10 largest US metros from Census data.”

“Show me nonfarm payroll growth month-over-month for 2025.”

Each of these would take 15 to 30 minutes of manual work. An agent handles them in seconds.

Where This Gets Powerful

The real value shows up when you combine sources. An agent can pull GDP growth from FRED, cross-reference it with employment data from BLS, and overlay demographic shifts from Census. That kind of multi-source analysis used to require a data team. Now it requires a well-worded prompt.

Researchers building reports, founders preparing pitch decks, journalists fact-checking claims: all of them need this data, and none of them want to learn three different API schemas to get it.

Setup

Connect AgentPatch to your AI agent to get access to the tools:

Claude Code

claude mcp add -s user --transport http agentpatch https://agentpatch.ai/mcp \
  --header "Authorization: Bearer YOUR_API_KEY"

OpenClaw

Add AgentPatch to ~/.openclaw/openclaw.json:

{
  "mcp": {
    "servers": {
      "agentpatch": {
        "transport": "streamable-http",
        "url": "https://agentpatch.ai/mcp"
      }
    }
  }
}

Get your API key at agentpatch.ai.

The Tools

AgentPatch provides four tools for government data:

  • fred-search: Find FRED series by keyword. No need to memorize series IDs.
  • fred-series-data: Pull time series data for any FRED series with date range filters.
  • census-data: Query American Community Survey tables by geography.
  • bls-data: Fetch BLS time series data by series ID or keyword.

Your agent chains these together as needed. Ask for unemployment data and it searches FRED, finds the right series, and pulls the values. Ask for a demographic breakdown and it routes to Census.

Wrapping Up

Government economic data is comprehensive but hard to access. FRED, Census, and BLS each hold pieces of the picture, and getting the full view means navigating three different systems. An AI agent with the right tools collapses that into a conversation. Try it at agentpatch.ai.

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