Project setup

🤖 MCP Chatbot Implementation Study Notes

Project Goal & Purpose

• Objective: Implement a CLI-based chatbot to demonstrate the interaction between MCP clients and servers.
• Scope: The project builds both an MCP client and a custom MCP server within a single environment to show how they work together.
• Context: In a typical real-world scenario, a project would usually focus on building either a client or a server.

System Architecture

• Interface: CLI-based chatbot.
• Data: A collection of fake documents stored only in memory (not persisted).
• Server Functionality: The custom MCP server includes two specific tools:
• Tool 1: Read the contents of a document.
• Tool 2: Update the contents of a document.
• Client Role: The small MCP client connects to the custom server to interact with the document tools.

Project Setup & Execution

• Starting Point: Download the CLI project. zip file.
• Configuration:
• Review README. md for setup instructions.
• Set the required API key in the . env file.
• Install dependencies (using uv or standard Python).
• Running the Project:
• Navigate to the project directory in the terminal.
• Execute the main script: uv run main. py (or python main. py).
• Expected Outcome: A chat prompt appears, and the application responds to simple queries (e. g. , "one plus one").

Takeaways

• The project implements a CLI-based chatbot to demonstrate the interaction between an MCP client and a custom MCP server.
• The custom MCP server provides specific tools for document management: reading and updating document contents.
• The MCP client connects to the server to utilize these defined document tools.
• All document data within the system is stored only in memory and is not persisted.