Model Context Protocol (MCP): Lets Implement an MCP server in Go
Model Context Protocol (MCP) is rapidly transforming how we interact with computers by enabling natural language instructions to handle complex tasks. As we stand at the beginning of this revolution, we’re witnessing fast-paced development in MCP tools and components. While a detailed introduction to MCP was covered in our previous post, here’s a quick refresher: MCP servers expose various capabilities (like resources, tools, and prompts) to clients. The clients can then use these capabilities in conjunction with Large Language Models (LLMs) to perform tasks.
Model Context Protocol (MCP): Building Bridges Between AI and Your World
Imagine having a brilliant personal assistant who’s incredibly smart but can only communicate through a mailbox - they can receive your letters and write back, but can’t directly interact with your computer, check your calendar, or access your files. That’s essentially the situation with today’s Large Language Models (LLMs) like Claude or GPT-4. Sure, they’re incredibly capable, but they’re often trapped behind an API, limited to text-in, text-out interactions. Enter the Model Context Protocol (MCP) - think of it as giving your AI assistant a complete office setup instead of just a mailbox.
Exploring Chain-of-Thought: Enhancing Problem-Solving in Large Language Models
LLMs are like enormous digital brains that have read a vast amount of text from the internet—books, articles, websites, and more. By doing so, they learn how to predict what word comes next in a sentence, which in turn helps them write essays, summarize texts, and even create poetry. However, despite their impressiveness in handling language, these models often struggled with tasks that required deeper levels of reasoning or problem-solving, such as math.