Github Repo: https://github.com/vpodorozh/mcp-git-...
Summary
In this session, Vladyslav Podorozhnyi introduces the Model Context Protocol (MCP) and demonstrates how to build an MCP server for executing Git commands. The conversation covers the importance of MCP in standardizing communication with AI models, the tools and resources it provides, and the process of creating and testing an MCP server. Vlad also discusses the architecture involving MCP, LLM, and client interactions, emphasizing the need for proper input and debugging to enhance functionality. The session concludes with a call for questions and further engagement.
Takeaways
MCP standardizes communication between applications and AI models.
It helps track conversations efficiently to avoid losing context.
MCP provides tools, prompts, and resources for developers.
Building an MCP server involves defining tools for specific commands.
Testing is crucial to ensure the MCP server functions correctly.
Connecting the MCP server to a client is essential for interaction.
Debugging is necessary to enhance the MCP server's functionality.
The architecture of MCP, LLM, and client is complex but powerful.
LLM acts as a decision maker in the interaction process.
Using MCP requires understanding and careful implementation.
Chapters
00:00 Introduction to MCP Server Build
04:54 Exploring MCP Server Functionality
09:16 Connecting MCP Server to Client
12:31 Debugging and Enhancing MCP Functionality
16:24 Understanding MCP Architecture and Workflow
Author:
Vladyslav Podorozhnyi / vladyslav-podorozhnyi
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