Model Context Protocol (MCP)

What is Model Context Protocol (MCP)?

Model Context Protocol (MCP) is a protocol designed to establish a communication channel between large language models (LLMs) and external tools or data sources, utilizing a client-server architecture and JSON-RPC 2.0 for messaging.

How to use MCP?

To use MCP, set up an MCP server using FastMCP or Low-Level APIs, and implement a client that communicates with the server via SSE or stdin. The server provides tools, resources, and prompts for the client to utilize.

Key features of MCP?

• Client-server architecture for communication between LLMs and external tools.
• Supports JSON-RPC 2.0 for messaging.
• Provides capabilities like tools, resources, and prompt templates.

Use cases of MCP?

1. Integrating LLMs with educational tools for language learning.
2. Enabling LLMs to access external data sources for enhanced responses.
3. Facilitating remote procedure calls between clients and servers in AI applications.

FAQ from MCP?

• What is the purpose of MCP?

MCP enables seamless communication between LLMs and external tools, enhancing their functionality.

• Is MCP easy to implement?

Yes, MCP provides both high-level and low-level APIs for flexibility in implementation.

• Can MCP be used for various applications?

Yes, MCP is versatile and can be adapted for different use cases in AI and data processing.