Architecture

LCQ uses a modular architecture that combines AI capabilities with blockchain data access through the Model Context Protocol (MCP).

System Overview

The LCQ framework consists of the following components:

1. Frontend UI: React-based interface for user interactions
2. Agent Framework: Core system that manages AI agents and their capabilities
3. MCP Integration Layer: Connects agents to the Solana blockchain via MCP
4. Agent Types: Specialized AI agents for different blockchain tasks
5. Data Storage: Caching and persistence layer for blockchain data

Data Flow

User → Frontend UI → Agent Framework → MCP Integration → Solana Blockchain
                                     ↓
                                Data Storage

1. User submits a query through the UI
2. The Agent Framework processes the query and routes it to the appropriate agent
3. The agent uses MCP to fetch relevant data from the Solana blockchain
4. Data is processed, analyzed, and formatted by the agent
5. Results are returned to the user through the UI

Model Context Protocol (MCP) Integration

The Model Context Protocol is central to LCQ's functionality:

• Secure Data Access: MCP provides a secure way for AI agents to access blockchain data
• Standardized Interface: Common methods for different blockchain operations
• Context Preservation: Maintains context across multiple queries
• Rate Limiting: Manages blockchain RPC requests efficiently

Agent Architecture

Each agent in LCQ follows a similar internal architecture:

Query Parser → Intent Recognition → Data Fetcher → Analysis Engine → Response Generator

1. Query Parser: Extracts key information from user queries
2. Intent Recognition: Identifies the user's goal and required data
3. Data Fetcher: Retrieves relevant blockchain data via MCP
4. Analysis Engine: Processes data to generate insights
5. Response Generator: Creates user-friendly responses with appropriate formatting

Technical Stack

LCQ is built using the following technologies:

• Frontend: React, Next.js, Tailwind CSS
• Backend: Node.js, Express
• AI: Large Language Models with MCP integration
• Blockchain: Solana RPC API via MCP
• Data Storage: Redis for caching, PostgreSQL for persistence

Extensibility

The LCQ architecture is designed for extensibility:

• Custom Agents: New agent types can be added by implementing the agent interface
• Additional Protocols: The framework can be extended to support blockchains beyond Solana
• Plugin System: Custom functionality can be added through plugins

Security Considerations

LCQ implements several security measures:

• No Wallet Access: Agents provide analysis and recommendations only, with no ability to execute transactions
• Data Validation: All blockchain data is validated before processing
• Rate Limiting: Prevents excessive RPC calls that could lead to service disruption
• Input Sanitization: User inputs are sanitized to prevent injection attacks