This MCP server corresponds to the MCP Tutorial Complete Guide repository, which provides structured material and example implementations for building and integrating MCP-based tools using Python and FastAPI. The server endpoint(s) expose a minimal MCP-driven interface designed for tutorials and demonstrations, enabling you to run, test, and experiment with practice MCP tool integrations, protocol features, and security best practices. Typical use involves starting the server in a Python virtual environment and then interacting with the exposed API to simulate tool execution requests, view responses, and verify error handling and state management across interactions. The repository also includes Jupyter notebooks and example projects (API Assistant, Data Manager, and File Handler) to illustrate practical MCP tool development, including REST-like API patterns, database interactions, and safe file operations that you can exercise against the running MCP server.

Prerequisites:

• Python 3.8+ installed on your system
• Git to clone the repository
• Optional: virtual environment support (venv)

1. Clone the repository git clone https://github.com/CarlosIbCu/mcp-tutorial-complete-guide.git cd mcp-tutorial-complete-guide

2. Set up a virtual environment (recommended) python -m venv venv

   macOS/Linux

   source venv/bin/activate

   Windows

   venv\Scripts\activate

3. Install dependencies pip install -r requirements.txt

4. Run the MCP server python -m mcp_tutorial_complete_guide.server

5. (Optional) Run Jupyter Lab for tutorials jupyter lab

Notes:

• The repository emphasizes Python with FastAPI and Pydantic; ensure your environment aligns with Python 3.8+ as indicated in the README.
• If the server module path differs in your setup, adjust the -m module_name portion accordingly.

Tips and common issues:

• Ensure your virtual environment is activated before installing dependencies to avoid conflicts with system packages.
• If you encounter port conflicts, override the PORT environment variable when starting the server (e.g., PORT=8080 python -m mcp_tutorial_complete_guide.server).
• The project includes notebooks for Fundamentals, Intermediate, and Advanced topics. Running Jupyter Lab allows interactive experimentation with MCP concepts such as state management, error handling, and protocol features.
• Check the repository structure for examples (api_assistant, data_manager, file_handler) to see concrete patterns for tool integration, REST-like APIs, and secure data handling.
• Review the requirements.txt and any optional extras to tailor the installation to your environment (e.g., database drivers, testing tools).

Environment variables and configuration options:

• PORT: Network port for the MCP server
• DEBUG: Enable verbose debugging output
• Other modules or endpoints may accept their own configuration; consult the tutorial notebooks for specific guidance on tool-specific settings.