Architecture Overview

YokoCTO employs a sophisticated architecture built on the Model Context Protocol (MCP), enabling seamless interaction between powerful AI reasoning models and specialized tools for crypto analysis.

Model Context Protocol (MCP)

The Model Context Protocol, pioneered by Anthropic AI, represents a revolutionary approach to AI agent architecture that enables:

• Efficient context management across multiple AI models

• Seamless integration of reasoning capabilities with specialized tools

• Dynamic memory management for extended conversations

• Enhanced performance through task-specific routing

[img] Diagram of the MCP architecture showing how context flows through the system (note: include a simplified version of the MCP diagram we created earlier)

Server-Client Architecture

YokoCTO implements a server-client architecture that separates compute-intensive AI operations from task-specific agent functions:

• MCP Server: Handles heavy computational loads including model inference, reasoning processes, and knowledge management

• MCP Client (Agent): Manages Twitter interactions, tool execution, and output formatting

This separation enables optimal resource allocation, enhanced reliability, and the ability to scale specific components independently as demand changes.

[img] Server-client architecture diagram (note: include the color-coded simplified architecture we created earlier)

Core Components

YokoCTO's architecture consists of several interconnected components:

• Core AI models for reasoning and analysis

• Knowledge bases (vector and graph databases)

• Input processing modules for Twitter and crypto data streams

• Tool integration layer for specialized functions

• Output generation systems for Twitter content