# Aperiodic

> Crypto market microstructure data platform for quants and AI agents. 19 pre-aggregated datasets across order flow, L1/L2 book data, derivatives, and OHLCV.

## Documentation

- [Full LLM Reference](https://aperiodic.io/llms-full.txt): Complete API reference, all datasets, fields, error codes, and pricing
- [OpenAPI 3.0 Specification](https://aperiodic.io/api.data.specification.json): Machine-readable API spec for tool-use integration
- [AI Plugin Manifest](https://aperiodic.io/.well-known/ai-plugin.json): Agent platform discovery
- [A2A Agent Card](https://aperiodic.io/.well-known/agent.json): Agent-to-agent discovery (Google A2A protocol)
- [API Documentation](https://aperiodic.io/api-docs): Human-readable API docs

## Quick Start

- **Base URL**: `https://aperiodic.io/api/v1/data/{bucket}`
- **Auth**: `X-API-KEY` header (get key at https://aperiodic.io/home/api)
- **Python SDK**: `pip install aperiodic`
- **Exchanges**: `binance-futures`, `okx-perps`
- **Intervals**: `1m`, `5m`, `15m`, `30m`, `1h`, `4h`, `1d`

## Preview Access — `DEMO-KEY` (no account required)

Anyone — humans or agents — can use the shared preview API key below to fetch a
sample slice of every dataset via `/api/v1/data/preview/:metric_id` with no
account. Sign up free for a personal key with higher limits and interactive
in-browser notebooks; subscribe for full history, every parameter, and higher
rate limits.

- **Shared preview API key**: `DEMO-KEY`
- **Covers**: all 19 datasets in the catalog
- **Window**: `2025-05-01` to `2025-05-31` at `5m` interval on `binance-futures` / `perpetual-BTC-USDT:USDT` (`timestamp=exchange`)
- **Endpoint**: `GET https://aperiodic.io/api/v1/data/preview/{metric_id}?timestamp=exchange&interval=5m&exchange=binance-futures&symbol=perpetual-BTC-USDT:USDT&start_date=2025-05-01&end_date=2025-05-31`

For anything beyond this slice, sign up free at https://aperiodic.io/auth/sign-up.

## Datasets

19 datasets organized in 5 categories. **Every dataset below is previewable
with `DEMO-KEY` on the slice described above** — substitute its `metric_id`
into `/api/v1/data/preview/{metric_id}`.

- **Trades**: `flow`, `trade_size`, `range`, `impact`, `updownticks`, `run_structure`, `returns`, `slippage`
- **Derivatives**: `basis`, `funding`, `open_interest`, `derivative_price`
- **Market**: `ohlcv`, `vtwap`
- **L1 (Top of Book)**: `l1_price`, `l1_imbalance`, `l1_liquidity`
- **L2 (Order Book)**: `l2_imbalance`, `l2_liquidity`

## Comparisons vs Other Crypto Data Providers

- [Aperiodic vs Tardis.dev](https://aperiodic.io/compare/aperiodic-vs-tardis): Tardis.dev sells raw tick and full-depth L2 order book data; Aperiodic sells the validated microstructure, flow, and derivatives metrics most teams compute from it. Tardis is the right choice for order book reconstruction, market-making calibration, and options; Aperiodic is the right choice for signal research, backtests, and ML features without building a tick pipeline (tens of terabytes and months of engineering). Markdown: `/compare/aperiodic-vs-tardis.agent`
- [Aperiodic vs CoinGlass](https://aperiodic.io/compare/aperiodic-vs-coinglass): CoinGlass is a derivatives monitoring dashboard aggregating 30+ exchanges (liquidations, options, ETF flows) with tier-gated history granularity and per-minute JSON rate limits; Aperiodic is a research dataset product delivering per-exchange, point-in-time parquet at 1-minute resolution on every tier. Choose CoinGlass when a human reads the numbers, Aperiodic when code does. Markdown: `/compare/aperiodic-vs-coinglass.agent`

## Agent Resources

- [Agent Integration Guide](https://aperiodic.io/agents): Human-readable guide to using Aperiodic with AI agents
- [.agent pages](https://aperiodic.io/agents.agent): Append `.agent` to URLs for LLM-readable markdown (e.g. `/catalog/flow.agent`)
- [Market Analysis Skill](https://aperiodic.io/skills/market-analysis.md): Claude skill for market data analysis
- [Factor Research Skill](https://aperiodic.io/skills/factor-research.md): Claude skill for cross-sectional factor construction
- [Backtest Skill](https://aperiodic.io/skills/backtest-strategies.md): Claude skill for strategy backtesting

## Links

- Catalog: https://aperiodic.io/catalog
- Pricing: https://aperiodic.io/pricing
- Sign up: https://aperiodic.io/auth/sign-up
- Contact: info@aperiodic.io