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introduction-to

This repository serves as a comprehensive guide to understanding and utilizing the Model Context Protocol (MCP) in AI applications. Below, you will find an overview of the course content, objectives, and links to additional resources.

Installation
Run this command in your terminal to add the MCP server to Claude Code.
Run in terminal:
Command
claude mcp add nisalgunawardhana-introduction-to-mcp

How to use

This MCP repository serves as an educational course for understanding and applying the Model Context Protocol (MCP). The content provides a guided path from MCP fundamentals to practical server and client demonstrations, best practices, troubleshooting, and advanced topics like building MCP with LLMs. Since this repository is a course with documentation and example materials rather than a live MCP server deployment, there isn't a single executable MCP server to run out-of-the-box. Instead, use the included Markdown documents, demos, and task resources to learn how MCP components interact and how tools and inspectors can be used to validate and experiment with MCP concepts. The course sections cover MCP basics, architecture, getting started, server and client development, debugging, and inspector usage, giving you a structured toolkit for MCP-enabled applications.

How to install

Prerequisites:

  • Basic familiarity with MCP concepts and a local development environment
  • Knowledge of your preferred language/tooling for MCP (Node.js, Python, etc.) depending on how you choose to implement servers/clients

Installation steps:

  1. Clone the repository: git clone https://github.com/nisalgunawardhana-introduction-to-mcp.git cd introduction-to-mcp

  2. Review the documentation:

    • Open the Markdown files under 1.introduction, 2.mcp-basics, 3.getting-started, and 4.server-development to understand the MCP setup and recommended practices.
  3. If you plan to run any sample code or demos locally, ensure your environment matches the language/tooling you intend to use (e.g., Node.js or Python). Install dependencies as needed for any included example projects (if provided in a later branch or subdirectory):

    • For Node.js examples (if you adapt any), run: npm install
    • For Python examples, run: python -m venv venv source venv/bin/activate pip install -r requirements.txt
  4. Follow the course’s Getting Started and Server Demo guides to configure and run any example MCP servers or clients you build based on the documentation.

Note: This repository primarily provides documentation and learning tasks. It may not include a ready-to-run MCP server package by default.

Additional notes

Tips and common issues:

  • MCP concepts are best understood by hands-on exploration of the server and client interaction flows described in the course materials.
  • If you plan to implement a local server, align your environment variables with any server or inspector configurations described in the docs.
  • When debugging, use the Inspector Guide and Debugging & Inspector resources to trace context, proposals, and model interactions.
  • Review the Troubleshooting section for common MCP integration issues such as context synchronization, latency considerations, and inspector connectivity.
  • Maintain clear separation between server-side MCP context provisioning and client-side request handling to simplify troubleshooting and testing.

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