# Data APIs for AI

- [Conclusion](https://docs.dapplooker.com/data-apis-for-ai/conclusion.md)
- [Contact Us](https://docs.dapplooker.com/data-apis-for-ai/contact-us.md)
- [x402 Payments](https://docs.dapplooker.com/data-apis-for-ai/x402-payments.md): Wallet-Based API Access for Agents and Autonomous Systems
- [Historical Market Data](https://docs.dapplooker.com/data-apis-for-ai/historical-market-data.md): Fetch historical daily metrics for any token, including USD price, trading volume, and market capitalisation. Ideal for backtesting, trend analysis, and building time-series visualisations.
- [Agent Intelligence](https://docs.dapplooker.com/data-apis-for-ai/agent-intelligence.md): Retrieve detailed metrics for specified AI agents, including market behaviour, technical indicators, and "smart money" movement patterns. Designed for deep analysis of agent strategies and
- [Token Directory](https://docs.dapplooker.com/data-apis-for-ai/token-directory.md): Get a complete list of indexed crypto tokens along with essential metadata. Useful for discovery, enumeration, and validation of active tokens across supported chains and protocols.
- [MCP / NLP driven Market Intelligence](https://docs.dapplooker.com/data-apis-for-ai/mcp-nlp-driven-market-intelligence.md): Run complex queries and extract chart-level insights using natural language. Powered by NLP and MCP-based APIs for agent-ready integration.
- [Staking Intelligence](https://docs.dapplooker.com/data-apis-for-ai/staking-intelligence.md): Provides real-time staking/unstaking data for tokens, including TVL, net staked, retention rates, and transaction-level insights - helping track participation, liquidity shifts, and on-chain sentiment
- [Trending Tokens](https://docs.dapplooker.com/data-apis-for-ai/trending-tokens.md): Access a list of tokens gaining real-time momentum based on aggregated market signals, user activity, and on-chain metrics. Ideal for surfacing high-velocity assets across tracked chains.
- [Hyperliquid Perp Trade Token Data](https://docs.dapplooker.com/data-apis-for-ai/hyperliquid-perp-trade-token-data.md): Provides real-time perpetual contract data for tokens on the Hyperliquid exchange. It returns live market prices, liquidity metrics, funding rates, and technical indicators to assist trading analysis.
- [Smart Money Trends](https://docs.dapplooker.com/data-apis-for-ai/smart-money-trends.md): Tracks net inflows/outflows by smart money wallets across 24h, 7d, and 30d periods. Helps identify accumulation or distribution patterns and spot tokens gaining attention from top market participants.
- [Unified Token Intelligence API](https://docs.dapplooker.com/data-apis-for-ai/unified-token-intelligence-api.md): Access consolidated token data through a single endpoint - combining market metrics, technical indicators, on-chain activity, and social sentiment.
- [ACP Activity Engine (Coming Soon)](https://docs.dapplooker.com/data-apis-for-ai/acp-activity-engine-coming-soon.md)
- [Live Hyperliquid Perp Strategy](https://docs.dapplooker.com/data-apis-for-ai/live-hyperliquid-perp-strategy.md): Provides real-time, AI-powerd perp trading strategies for Hyperliquid markets. gives actionable strategies with clear entry zones, risk parameters, leverage guidance, and execution-ready action object
- [GET: Agent Metadata](https://docs.dapplooker.com/data-apis-for-ai/get-agent-metadata.md)


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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.dapplooker.com/data-apis-for-ai.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.