Quick Selection
Choose your path based on your primary needs:| I want to… | Recommended Path |
|---|---|
| Get token prices and trading data | Data User |
| Detect transaction risks and analyze addresses | Compliance User |
| Let AI query on-chain data | AI Builder |
Data User
Use Cases
Developers who need to obtain on-chain data for display, analysis, or trading decisions. Typical scenarios:- Display real-time token prices in dApps
- Build market dashboards or data analytics tools
- Monitor position changes of specific wallets
- Develop trading bots to get market data
- DeFi application developers
- Market data display platforms
- On-chain data analysts
- Trading bot developers
Recommended Path
Understand Data Models
Read Data Concepts to understand ChainStream’s data structure
Call Token API
View Token API Reference to get price and token information
Hands-on: Price Alert
Follow the Price Alert Bot Tutorial to build a complete application
Core Capabilities
You will use the following capabilities:- Real-time price data (WebSocket push)
- Multi-chain token information queries
- Trading and position data
- Smart Money wallet tracking
Estimated time: Completing the recommended path takes approximately 1-2 hours
Compliance User
Use Cases
Teams that need to assess transaction risks or analyze address security. Typical scenarios:- Detect if user deposits come from high-risk addresses
- Analyze wallet address historical behavior
- Generate transaction risk assessment reports
- Integrate risk control flows into business systems
- Exchange compliance teams
- Wallet security teams
- Risk control system developers
Recommended Path
Understand KYT/KYA
Read Security Compliance Overview to understand risk control capabilities
Call Risk Assessment API
View KYT API Reference to understand transaction risk assessment interfaces
Hands-on: Deposit Risk Control
Follow the Deposit Risk Control Integration Tutorial to implement the complete flow
Core Capabilities
You will use the following capabilities:- KYT transaction risk assessment (returns risk scores and labels)
- KYA address profiling (address type, historical behavior)
- Risk label system (configurable risk rules)
Estimated time: Completing the recommended path takes approximately 2-3 hours
AI Builder
Use Cases
Developers who want AI Agents to query and understand on-chain data. Typical scenarios:- Let Claude/GPT answer on-chain data questions
- Build AI assistants that understand crypto markets
- Integrate on-chain data queries into AI workflows
- AI Agent developers
- Automated trading system developers
- LLM application developers
- MCP integration developers
Recommended Path
Understand AI Capabilities
Read AI Infrastructure Overview to understand the MCP protocol
Configure MCP Server
Follow the MCP Setup Guide to complete integration
Hands-on: AI Assistant
Follow the AI Trading Assistant Tutorial to build a complete application
Core Capabilities
You will use the following capabilities:- MCP Server integration (supports Claude Desktop and other clients)
- AI-friendly toolset (structured output)
- Natural language queries (e.g., “Query ETH price in the last 24 hours”)
Estimated time: Completing the recommended path takes approximately 1-2 hours
Next Steps
Based on your chosen path, go to the corresponding documentation module to start learning.Data User
Start with Data Concepts
Compliance User
Start with Security Compliance
AI Builder
Start with AI Infrastructure