Unit1 recap

Model Context Protocol (MCP)

The MCP is a standardized protocol designed to connect AI models with external tools, data sources, and environments. It addresses the limitations of existing AI systems by enabling interoperability and access to real-time information.

Key Concepts

Client-Server Architecture

MCP follows a client-server model where clients manage communication between users and servers. This architecture promotes modularity, allowing for easy addition of new servers without requiring changes to existing hosts.

Components

Host

The user-facing AI application that serves as the interface for end-users.

Client

A component within the host application responsible for managing communication with a specific MCP server. Clients maintain 1:1 connections with servers and handle protocol-level details.

Server

An external program or service that provides access to tools, data sources, or services via the MCP protocol. Servers act as lightweight wrappers around existing functionalities.

Capabilities

Tools

Executable functions that can perform actions (e.g., sending messages, querying APIs). Tools are typically model-controlled and require user approval due to their ability to perform actions with side effects.

Resources

Read-only data sources for context retrieval without significant computation. Resources are application-controlled and designed for data retrieval similar to GET endpoints in REST APIs.

Prompts

Pre-defined templates or workflows that guide interactions between users, AI models, and available capabilities. Prompts are user-controlled and set the context for interactions.

Sampling

Server-initiated requests for LLM processing, enabling server-driven agentic behaviors and potentially recursive or multi-step interactions. Sampling operations typically require user approval.

Communication Protocol

The MCP protocol uses JSON-RPC 2.0 as the message format for communication between clients and servers. Two primary transport mechanisms are supported: stdio (for local communication) and HTTP+SSE (for remote communication). Messages include requests, responses, and notifications.

Discovery Process

MCP allows clients to dynamically discover available tools, resources, and prompts through list methods (e.g., tools/list). This dynamic discovery mechanism enables clients to adapt to the specific capabilities each server offers without requiring hardcoded knowledge of server functionality.

MCP SDKs

Official SDKs are available in various programming languages for implementing MCP clients and servers. These SDKs handle protocol-level communication, capability registration, and error handling, simplifying the development process.

Gradio Integration

Gradio allows easy creation of web interfaces that expose capabilities to the MCP protocol, making it accessible for both humans and AI models. This integration provides a human-friendly interface alongside AI-accessible tools with minimal code.

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