Tag: Ai

TOON Format: Token-Oriented Object Notation for LLM-Friendly Data Exchange

Introduction

If you build systems that pass structured data through large language models (LLMs), you eventually hit the same set of issues:

Standardizing AI Context: the Model Context Protocol

The Model Context Protocol (MCP) server acts as a centralized context management backend for advanced AI applications.

Unlike traditional session or prompt-based approaches, the MCP server manages a persistent, structured context that can be queried, updated and synchronized across distributed AI components and user sessions. By providing a standard API for serializing, retrieving and sharing context, the MCP server enables seamless interoperability between different models, services and clients. This is particularly important in multi-agent systems, long-running workflows or environments where state continuity and context portability are required.