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1. Create an account

Sign up at financialdatasets.ai and generate your API key from the dashboard.

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2. Make your first request

Every request needs two things:
  • Your API key in the X-API-KEY header
  • A ticker query parameter
import requests

headers = {"X-API-KEY": "your_api_key_here"}

url = "https://api.financialdatasets.ai/financials/income-statements?ticker=AAPL&period=annual&limit=4"

response = requests.get(url, headers=headers)
data = response.json()

for stmt in data["income_statements"]:
    print(f"{stmt['report_period']}: Revenue = ${stmt['revenue']:,.0f}")

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3. Explore more endpoints

Now that you have the basics, try a few more calls: 
import requests

# authenticate
headers = {"X-API-KEY": "your_api_key_here"}

# get the real-time price snapshot for NVDA
url = "https://api.financialdatasets.ai/prices/snapshot?ticker=NVDA"
response = requests.get(url, headers=headers)

# parse the snapshot from the response
snapshot = response.json()["snapshot"]
print(f"NVDA: ${snapshot['close']}")

import requests

# authenticate
headers = {"X-API-KEY": "your_api_key_here"}

# get company facts for Tesla
url = "https://api.financialdatasets.ai/company/facts?ticker=TSLA"
response = requests.get(url, headers=headers)

# parse company facts from the response
facts = response.json()["company_facts"]
print(f"{facts['name']} — {facts['sector']}, {facts['industry']}")

import requests

# authenticate
headers = {"X-API-KEY": "your_api_key_here"}

# get the 5 most recent insider trades for Apple
url = "https://api.financialdatasets.ai/insider-trades?ticker=AAPL&limit=5"
response = requests.get(url, headers=headers)

# parse insider trades from the response
trades = response.json()["insider_trades"]
for t in trades:
    print(f"{t['name']}: {t['transaction_shares']} shares on {t['transaction_date']}")

import requests

# authenticate
headers = {"X-API-KEY": "your_api_key_here"}

# use the screener to find companies with revenue > $50B
url = "https://api.financialdatasets.ai/financials/search/screener"
body = {
    "filters": [
        {"field": "revenue", "operator": "gt", "value": 50000000000}
    ],
    "limit": 10
}
response = requests.post(url, json=body, headers=headers)

# parse the results from the response
results = response.json()["results"]
for r in results:
    print(f"{r['ticker']}: Revenue = ${r['revenue']:,.0f}")

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4. What’s next?

Financial Statements

Income statements, balance sheets, and cash flow statements.

Stock Prices

Historical and real-time price data.

SEC Filings

10-K, 10-Q, 8-K filings with section-level extraction.

MCP Server

Connect your AI assistant directly to our data.