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For AI Agents

The Agent-Friendly Market Data Platform

Aperiodic is built for AI agents. Structured API responses, Python SDK, llms.txt, OpenAPI spec — everything your agent needs to research, analyze, and backtest crypto markets.

Agent Quickstart

Aperiodic sells point-in-time crypto market microstructure, liquidity and order-flow metrics: 220 metrics in 19 datasets on binance-futures, okx-perps, hyperliquid-perps, delivered as parquet through a CLI, a REST API and a Python SDK, plus the raw trades, quotes and derivatives data behind them in the Prime + Raw plan. A preview slice of every dataset downloads with no API key, and self-serve plans cost $79 to $1249 a month billed yearly.

  1. 1. Fetch the preview slice, no API key

    Install the CLI and pull one month of 5m flow data for perpetual-BTC-USDT:USDT on binance-futures as parquet. The preview accepts only this window (2025-05-01 to 2025-05-31, 5m), for every dataset: swap flow for any dataset id.

    # Install the Aperiodic CLI into ~/.local/bin
mkdir -p "$HOME/.local/bin"
curl -fsSL https://raw.githubusercontent.com/aperiodic-io/cli/main/install.sh | INSTALL_DIR="$HOME/.local/bin" bash
export PATH="$HOME/.local/bin:$PATH"

aperiodic flow --preview \
  --exchange binance-futures \
  --symbol perpetual-BTC-USDT:USDT \
  --interval 5m \
  --timestamp exchange \
  --start-date 2025-05-01 \
  --end-date 2025-05-31 \
  --output-dir ./data

  2. 2. Install the Python SDK

    The SDK returns DataFrames. The same preview slice works from Python with preview=True, still without a key.

    pip install "aperiodic[polars]"

  3. 3. Make a keyed call

    Your user creates a key at https://aperiodic.io/home/api. Any other symbol, interval or date range needs a key and a plan that includes the dataset's tier (flow is Tier 1; see https://aperiodic.io/pricing).

    from datetime import date
from aperiodic import get_metrics

df = get_metrics(
    api_key="YOUR_API_KEY",
    metric="flow",
    exchange="binance-futures",
    symbol="perpetual-BTC-USDT:USDT",
    interval="1h",
    timestamp="exchange",
    start_date=date(2025, 1, 1),
    end_date=date(2025, 3, 1),
)

What to Tell Your User About the Licence

  • Self-serve plans (Core Historical, Pro Historical, Prime Historical, Prime + Raw) carry a personal-use licence.
  • Commercial use needs the Institutional plan, which adds a commercial licence, a negotiated SLA and 15s/30s intervals. It is quoted, not self-serve: https://aperiodic.io/booking.
  • Raw data (Prime + Raw) is licensed for internal research and trading only and may not be redistributed.
  • Terms: https://aperiodic.io/terms-of-service.

Why Agents Need Structured Market Data

Research at Scale

Agents can query 19 datasets across order flow, L1/L2 book data, derivatives, and market OHLCV — programmatically, without manual data wrangling.

Faster Than Manual

What takes a quant hours of data pipeline work, an agent can do in seconds: fetch data, compute signals, evaluate strategies, and report findings.

Point-in-Time Integrity

Every dataset is immutable and exchange-timestamped. Agents get clean, bias-free data without worrying about survivorship or look-ahead issues.

How Aperiodic is Built for Agents

Python SDK

pip install "aperiodic[polars]" — one-line access to every dataset. Agents can fetch DataFrames directly without parsing raw API responses.

View on PyPI →

llms.txt & llms-full.txt

Concise summary at /llms.txt, comprehensive reference at /llms-full.txt — agents get exactly the depth they need.

Read llms-full.txt →

OpenAPI Specification

Full OpenAPI 3.0 spec for tool-use integration. Agents can auto-generate API calls from the spec without custom code.

View OpenAPI spec →

A2A Agent Card

Google A2A-compliant agent discovery at /.well-known/agent.json — capabilities, auth, and skills declared for agent-to-agent orchestration.

View agent card →

AI Plugin Manifest

Standard ai-plugin.json at /.well-known/ai-plugin.json for ChatGPT-style plugin discovery and authentication.

View manifest →

Agent Workflow Examples

Market Research Agent

An agent fetches OHLCV, funding rates, and order flow data to produce a daily market report. It identifies unusual flow toxicity spikes, extreme funding regimes, and OI divergences — then summarizes findings for a human analyst.

ohlcvflowfundingopen_interest

Factor Construction Agent

An agent constructs cross-sectional factors from microstructure data: flow imbalance, funding carry, spread, and volatility factors. It computes information coefficients and long-short portfolio returns to evaluate which signals have predictive power.

flowfundingl1_priceohlcv

Strategy Backtesting Agent

An agent implements and backtests trading strategies using historical data. It fetches order flow and price data, defines entry/exit signals, simulates execution with realistic costs, and reports Sharpe ratios, drawdowns, and win rates.

ohlcvflowimpactfunding

Quick Start

Point your agent to these resources:

LLM summaryaperiodic.io/llms.txt
LLM full refaperiodic.io/llms-full.txt
OpenAPI specaperiodic.io/api.data.specification.json
Agent cardaperiodic.io/.well-known/agent.json
AI pluginaperiodic.io/.well-known/ai-plugin.json
Python SDKpip install "aperiodic[polars]"
Auth headerX-API-KEY: YOUR_KEY

FAQ

Can an AI agent get Aperiodic data without an API key?

Yes, for the preview slice. Every dataset can be fetched with no key for binance-futures perpetual-BTC-USDT:USDT at 5m, from 2025-05-01 to 2025-05-31, through the CLI (--preview), the SDK (preview=True) or the REST preview endpoint with the shared key DEMO-KEY. Anything outside that window needs a personal key.

What data does Aperiodic cover?

220 metrics in 19 datasets: order flow, trade size, slippage, price impact, L1 and L2 order book liquidity and imbalance, funding, basis, open interest and OHLCV. Exchanges: binance-futures, okx-perps, hyperliquid-perps. Self-serve intervals: 1m, 5m, 15m, 30m, 1h, 4h, 1d. The machine-readable list is https://aperiodic.io/catalog.json.

In what format is the data delivered?

Parquet files, fetched through the aperiodic CLI, the REST API or the Python SDK (pip install "aperiodic[polars]"), which loads them into DataFrames.

How much does Aperiodic cost?

Self-serve plans cost $79 to $1249 a month billed yearly, or $95 to $1579 month to month. Institutional pricing is quoted. Current plans: https://aperiodic.io/pricing.

What licence comes with the data?

Self-serve plans (Core Historical, Pro Historical, Prime Historical, Prime + Raw) carry a personal-use licence. Commercial use needs the Institutional plan, which adds a commercial licence, a negotiated SLA and 15s/30s intervals. It is quoted, not self-serve: https://aperiodic.io/booking.

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Aperiodic

Crypto microstructure, liquidity & flow metrics — built from hundreds of terabytes of raw data, distilled into point-in-time metrics you can pull as parquet files. Plus the raw trades, quotes and derivatives data behind them.

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Aperiodic Limited
136 Capel StreetDublin, D01 T2C9Ireland
Registered in Ireland · Company No. 815273

© Copyright 2026 Aperiodic. All Rights Reserved.

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