🌾 New Data Expansion: Agro Commodities (Rice, Coconut, Palm Oil) & Retail Pricing History APIs are now live! Explore Datasets →
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● Modernizing Equities, Agro Commodities & Retail Pricing

Financial, Agro Commodity & Retail Market Data API.

Institutional-grade tick and spot data for US Stocks, Options, Futures alongside physical Agro Commodities (Rice, Coconut, Palm Oil, Crops) and multi-year Retail Pricing History via REST, WebSockets, and S3 Flat Files.

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🏛️ NYSE / NASDAQ
⚡ CME GLOBEX
🌾 AGRI-EXCHANGES (ICDX / CBOT)
🥥 TROPICAL COMMODITY AUCTIONS
🛒 RETAIL PRICING CONSORTIUM
🪙 COINBASE
Client Request • SDK Code
from pota import PotaClient

client = PotaClient(api_key="POTA_LIVE_KEY")

# Fetch spot prices & farmgate benchmarks for Rice and Coconut
rice = client.agro.get_commodity_spot(
    commodity="RICE_PREMIUM",
    grade="LONG_GRAIN",
    region="SE_ASIA"
)
coconut = client.agro.get_commodity_spot(
    commodity="COCONUT_COPRA",
    timespan="daily"
)

print(f"Rice Benchmark: ${rice.price_per_mt}/MT (Change: {rice.change_pct}%)")
print(f"Coconut Copra: ${coconut.price_per_mt}/MT")
JSON Response Preview (14ms Latency)
{
  "status": "OK",
  "commodity": "RICE_PREMIUM",
  "benchmark_spec": "5% Broken Milled Rice",
  "currency": "USD",
  "price_per_metric_ton": 582.50,
  "price_per_kg": 0.5825,
  "effective_date": "2026-10-12",
  "physical_volume_mt": 14500,
  "change_24h_pct": +1.25,
  "farmgate_spread": 18.4
}
120+
Agro Crops & Physical Feeds
10+ Yrs
Retail Price History Archive
34,000+
US Stocks & Options Tickers
< 15ms
Global Normalized Latency
Integrated Delivery

One Unified API for Financial & Physical Markets

Access stocks, options, agricultural commodity spot prices, and retail time-series without switching providers.

RESTful & WebSocket Feeds

Low-latency programmatic access to tick-level equity trades, crypto spot books, and live wholesale crop auction updates.

View API endpoints →

Daily S3 Flat Files

Automated partitioning of daily historical retail grocery prices, supermarket barcode histories, and physical commodity warehouse receipts in CSV/Parquet.

Browse S3 datasets →

SQL Analytics Warehouse

Execute complex queries comparing farmgate crop yields, wholesale coconut/rice benchmark trends, and retail consumer price spreads.

Request SQL access →
Market data for all

Comprehensive Coverage Matrix

From global equities and OPRA options to physical agricultural crops and retail scanner history.

🌾 Agro Commodities & Crops

Rice, Coconut & Soft Commodities

Physical cash spot rates, farmgate auction benchmarks, and export FOB prices for Milled Rice, Coconut (Copra & Crude Coconut Oil), Palm Oil (CPO), Coffee, Cocoa, Corn, and Soybeans.

85+
Agro Varieties
Daily/Spot
Frequency
15+ Yrs
Historical Series
🛒 Consumer Intelligence

Retail Pricing History

Historical daily and weekly supermarket shelf prices, consumer staple baskets (food, grains, FMCG), regional inflation trackers, and farm-to-shelf margin spread analytics.

500K+
Retail SKUs
Since 2014
History
Store/City
Granularity
📈 Equities

US Stocks & ETFs

Real-time and historical tick-by-tick trades and NBBO quotes from all US exchanges and dark pools.

34,000+
Tickers
Since 2003
History
350B+
Data Points
⚡ Derivatives

Options Contracts

Full 16-exchange OPRA feed with Greeks, implied volatility, Open Interest, and millisecond trade tracking.

1.8M+
Contracts
Since 2012
History
720B+
Data Points
📊 Futures

Commodity Futures (CME Globex)

Direct CME, CBOT, NYMEX, and COMEX streaming data for grains, energy, metals, and financial contracts.

380K+
Contracts
Tick Level
Resolution
260M+
Data Points
🌐 Forex & Crypto

Currencies & Crypto

Forex pairs and cryptocurrency markets with tick-by-tick precision, cross-currency rates, and liquidity depth.

1,800+
FX Pairs
2,200+
Crypto Pairs
24/7
Streaming
Real markets. Any AI tool.

Pull financial, agro & retail data into your AI agents.

One instruction, and your agent understands the pota.ai API and handles the setup. Model Context Protocol (MCP) server allows Claude Code, Cursor, and ChatGPT to analyze agricultural supply trends and retail inflation automatically.

Explore MCP Server Setup →
>_ agent prompt example
$ Read https://pota.ai/docs/llms.txt. Compare the 12-month historical retail pricing trend of premium rice against regional coconut copra spot prices and plot the spread.