AI BriefingEverything About MCP (Model Context Protocol)
Key point
MCP is a connection protocol that helps AI models access external data and tools in a standardized way.
Details
MCP (Model Context Protocol) is a standardized way to connect AI models with data sources and tools. Like a USB-C port that connects various devices, it acts as a 'universal connector' that allows different AI models to access the same tools and data.
MCP operates based on a Client-Server structure, divided into three core components.
- Client (Client/Host): An AI model such as Claude or GPT, or an application that needs external tools, such as Claude Desktop or a code editor.
- Protocol: The core standard that defines the format of requests and responses and manages security, error handling, and data formats.
- Server: A lightweight program that provides resources needed by AI, such as databases, YouTube, weather, or stock information.
Existing AI models had constraints in obtaining real-time information or using external tools due to the limitations of their training data. MCP resolves this gap, evolving AI from an isolated system into a connected application.
Key features include the following core capabilities.
- Resources: Sharing data and content with AI models
- Prompts: Creating reusable templates for consistent interactions
- Tools: Performing actions by AI models through services
- Sampling: The ability for services to request information from AI models
- Transports: Efficient connections between clients and servers
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