Free public beta — 1 GB/month free

Ask Claude anything about
the US government

330+ datasets from 30 federal agencies — cross-linked by legal entity, geography, and time since 2010. Includes text similarity search across SEC filings and the Federal Register. Query everything in plain English via Claude Desktop, or directly from Python with one pip install.

MCP-compatible client · AskAmerica
You
Which Senate candidates raised the most money in 2024,
and where did it come from?
Claude
Here are the top 2024 Senate fundraisers by total receipts: Jon Tester (D-MT) $12.4M — 68% small donors, 32% PAC Ted Cruz (R-TX) $9.8M — 41% small donors, 59% PAC Sherrod Brown (D-OH) $9.1M — 72% small donors, 28% PAC Tester's race was the most expensive Senate contest of the cycle. Want a breakdown by contribution size or committee type?
pip install 'askamerica[engine]'
Also works from Python, Node, Java, DBeaver

330+ datasets.
30 agencies. One key.

Updated daily from primary government sources, with history back to 2010. All schemas cross-linked by legal entity, geography, and time. No API keys per dataset — one AskAmerica key accesses everything.

🏦
SEC Filings & Market Data
16 datasets — 10-K, 10-Q, 8-K filings, XBRL financials, insider transactions, institutional holdings, company facts, and end-of-day stock prices for all EDGAR filers. Includes text similarity search across footnotes and MD&A sections. Updated daily.
sec.*
🗳️
FEC Campaign Finance
14 datasets — every contribution, expenditure, and independent expenditure reported to the FEC. Candidates, committees, PACs, and super PACs.
fec.*
🌦️
NOAA Weather
14 datasets — daily observations from 100,000+ stations (GHCND), storm events, drought monitor, NWS forecasts, and EPA air quality. Since 2010.
weather.*
📊
Census Bureau
44 datasets — ACS 5-year estimates, decennial census, population estimates, business dynamics, county business patterns, and commuter flows at every geography.
census.*
📈
Economic Indicators
45 datasets — BLS jobs and CPI, BEA GDP and PCE, Federal Reserve rates and M2, Treasury yields, and Census trade flows. Monthly and quarterly.
econ.*
🔵
Federal Register
Every federal rule, proposed rule, and notice — full text, agency metadata, CFR citations, and comment periods. Supports text similarity search across the full document corpus. Updated daily.
fedregister.*
🔒
Cyber Vulnerabilities
13 datasets — NIST NVD CVE records, CVSS scores, CPE matches, OSV open-source advisories, and CISA remediation deadlines. Updated daily.
cyber_vuln.*
⚠️
Cyber Threat Intelligence
12 datasets — MITRE ATT&CK techniques and groups, CISA known exploited vulnerabilities, IOC feeds, and NIST/CIS security controls.
cyber_threat.*
EIA Energy
18 datasets — electricity generation and retail sales, natural gas, petroleum, coal, and renewables by state and fuel type. Includes MSHA mine safety data.
energy.*
🏥
Health (FDA / CDC / CMS)
29 datasets — FDA drug approvals and adverse events, CDC Wonder mortality, CMS Open Payments, ClinicalTrials.gov, and RxNorm drug codes.
health.*
🎓
Education (NCES)
23 datasets — IPEDS college finance and outcomes, Common Core K-12 school statistics, CRDC civil rights data, NAEP assessments, and College Scorecard.
edu.*
🚨
Crime (FBI / BJS)
17 datasets — FBI UCR and NIBRS offense and arrest data by agency and state, plus BJS victimization surveys. Property crime, violent crime, and more.
crime.*
🗺️
Geographic Boundaries
32 datasets — Census TIGER/Line boundaries, FIPS codes, HUD crosswalks, and USGS place names for states, counties, tracts, ZCTAs, places, and CBSAs.
geo.*
🌲
Federal Lands
21 datasets — USFS national forests and timber sales, NPS units, BLM field offices, forest inventory, and ONRR mineral and energy revenues.
lands.*
💡
Patents (USPTO)
11 datasets — US patent and trademark filings, grants, citations, inventors, and assignees from the USPTO bulk data archive.
patents.*
📉
CFTC Derivatives
8 datasets — swap trade repository data, commitments of traders, large trader positions, and cleared derivatives from the Commodity Futures Trading Commission.
cftc.*
📋
Reference Tables
5 datasets — GLEIF legal entity identifiers, FIGI instrument codes, SEC company tickers, and NAICS/SIC codes for joining across schemas.
ref.*
🔤
Econ Reference
7 datasets — BLS area, industry, and occupation classification tables plus NIPA accounts and Federal Reserve series codes for joining with economic data.
econ_reference.*

Zero infrastructure.
Pick your interface.

AskAmerica handles ingestion, formatting, and serving. Choose how you want to query.

01 —
Get a free API key
Enter your email below. Receive a 6-digit code. No password, no credit card.
02 —
Install the MCP server
Download the native installer for macOS, Windows, or Linux — bundled JRE, no Java or Python required. Or: pip install 'askamerica[mcp]'
03 —
Configure Claude Desktop
Enter your API key in the installer and click Configure. AskAmerica registers itself as an MCP tool — no config files to edit.
04 —
Ask in plain English
Claude writes and runs the SQL for you. Ask about any agency, company, geography, or time range — no SQL required on your end.
01 —
Get a free API key
Enter your email below. Receive a 6-digit code. No password, no credit card.
02 —
pip install askamerica
Python 3.8+. pip install 'askamerica[engine]' then askamerica install-engine to pull the query engine once. Java 11+ required.
03 —
Set your API key
Run askamerica login to store your key, or pass it directly: aa.configure(api_key="...")
04 —
Query → DataFrame
Call aa.query("SELECT ...") and get a pandas DataFrame back. Standard SQL across all 330+ datasets.
01 —
Get a free API key
Enter your email below. Receive a 6-digit code. No password, no credit card.
02 —
Download the JAR
Grab askamerica-engine.jar from the GitHub releases page. A single fat JAR — no other dependencies.
03 —
Configure your client
Point DBeaver, IntelliJ, or any JDBC client at the JAR. Use the URL jdbc:askamerica:source=sec,geo and your API key as the password.
04 —
Write SQL
Query any dataset from Node, Go, Java, or any language with a JDBC bridge. Pay only for bytes scanned — free tier: 1 GB/month.

Start free.
Scale when you're ready.

All plans include every dataset. You pay for bytes scanned, not seats.

Free
$0/mo
1 GB / month
  • All datasets included
  • Email OTP auth — no password
  • pandas DataFrame output
  • Community support
Get free key →
Pro
$99/mo
500 GB / month
  • Everything in Starter
  • 500 GB monthly quota
  • Priority support
  • Early access to new datasets
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Get started.
Your way.

Same data, same API key — choose the client that fits your workflow.

Recommended

Native installer

Bundled JRE — no Java, no Python, no config files. Open the app, enter your API key, click Configure. Works with Claude Desktop and any other MCP-compatible client.

Or via pip: pip install 'askamerica[mcp]' then askamerica mcp-config.

Claude Desktop gains these tools
list_schemas    → what datasets are available?
list_tables     → what tables are in fec?
describe_table  → what columns does contributions have?
query           → run any SQL and return results

Claude calls these automatically — you just ask questions in plain English. No SQL required on your end.

Developer

pip install

One package, zero boilerplate. Returns a pandas DataFrame or a raw JDBC connection — JPype is managed internally, never exposed.

setup
pip install 'askamerica[engine]'
askamerica install-engine   # downloads JAR once
askamerica login            # set API key

Python 3.8+. Java 11+ must be on your PATH (or set JAVA_HOME).

one-liner → DataFrame
import askamerica as aa

df = aa.query("""
  SELECT company_name, value_dollars
  FROM sec.financial_facts
  WHERE canonical_name = 'Revenue'
  ORDER BY value_dollars DESC
  FETCH FIRST 10 ROWS ONLY
""")
print(df)
raw JDBC connection
conn = aa.connect()
rs = conn.createStatement().executeQuery(
    "SELECT cik, company_name FROM sec.filing_metadata"
    " ORDER BY filing_date DESC FETCH FIRST 5 ROWS ONLY")
while rs.next():
    print(rs.getString("company_name"))
conn.close()
Any language

Raw JAR

A single fat JAR — use from Node, Go, Java, DBeaver, or any JDBC client. No other dependencies.

↓ askamerica-engine.jar
DBeaver connection settings
JDBC URL:     jdbc:askamerica:source=geo,sec
Driver JAR:   askamerica-engine.jar
Driver class: org.apache.calcite.adapter
              .askamerica.AskAmericaDriver
Username:     (leave blank)
const { createConnection } = require('jdbc');
const conn = await createConnection({
  url: 'jdbc:askamerica:source=sec,geo',
  drivername: 'org.apache.calcite.adapter
    .askamerica.AskAmericaDriver',
  classpath: ['./askamerica-engine.jar']
});
const rows = await conn.query(
  'SELECT cik, company_name FROM sec.filing_metadata FETCH FIRST 5 ROWS ONLY');
// go-jdbc wraps the JVM via CGo
db, _ := sql.Open("jdbc",
  "jdbc:askamerica:source=sec,geo")
rows, _ := db.Query(
  "SELECT cik, company_name FROM sec.filing_metadata FETCH FIRST 5 ROWS ONLY")
AskAmericaDriver driver = new AskAmericaDriver();
Connection conn = driver.connect(
    "jdbc:askamerica:source=sec,geo,econ",
    new Properties());
ResultSet rs = conn.createStatement().executeQuery(
    "SELECT cik, company_name FROM sec.filing_metadata FETCH FIRST 5 ROWS ONLY");

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