Merge pull request #53 from csabakecskemeti/patch-2

Create unit1-recap.mdx

Author: burtenshaw

units/en/_toctree.yml

@@ -25,6 +25,8 @@
     title: MCP Clients
   - local: unit1/gradio-mcp
     title: Gradio MCP Integration
+  - local: unit1/unit1-recap
+    title: Unit 1 Recap
   - local: unit1/certificate
     title: Get your certificate!
 

units/en/unit1/unit1-recap.mdx

@@ -0,0 +1,45 @@
+# 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.