This MCP server provides a Python-based implementation of the Model Context Protocol (MCP). It exposes a set of tools and resources that clients can discover, inspect, and interact with via standard MCP methods. Developers can test server capabilities using the built-in inspector tooling, send capability queries, and invoke tools exposed by the server in a structured, interoperable manner. The server is designed to work with common MCP clients and agents, enabling structured communication, capability description, and secure interaction with AI models and external resources.

To use the server, start it with the Python module name learn_model_context_protocol_server. Once running, you can query the server’s capabilities, list available tools, and invoke specific tools with properly formatted MCP requests. If you’re using editor-integrated inspectors or IDE plugins, connect to the host/port you configured to browse capabilities, test calls, and inspect responses. For production use, integrate with your agent workflows, ensuring you configure environment variables for host/port and security settings as appropriate.

Prerequisites:

• Python 3.8 or later installed on your system
• Access to a terminal or command prompt
• Basic familiarity with Python packaging and CLI usage

Steps:

1. Clone the repository: git clone https://github.com/packtpublishing/learn-model-context-protocol-with-python.git cd learn-model-context-protocol-with-python

2. Create and activate a virtual environment (recommended):

   • On Windows: python -m venv .venv && ..venv\Scripts\activate
   • On macOS/Linux: python3 -m venv .venv && source .venv/bin/activate

3. Install dependencies (if a requirements.txt is provided) or install via pip from the project namespace: pip install -r requirements.txt

   or, if there is a setup.py / pyproject.toml, install the package in editable mode:

   pip install -e .

4. Run the MCP server (adjust module name if needed): python -m learn_model_context_protocol_server

5. Verify the server is listening (default port 8080 unless overridden by MCP_HOST/MCP_PORT): curl http://localhost:8080/.well-known/mcp

6. Optional: set environment variables as described in the mcp_config section before starting the server.

Tips and common issues:

• Ensure Python 3.8+ is used; some MCP features depend on newer language features.
• If the server fails to start, check logs for missing dependencies or misconfigured environment variables (MCP_HOST, MCP_PORT).
• Use a virtual environment to avoid conflicts with system packages.
• When testing locally, avoid exposing MCP_PORT directly to the internet without proper authentication and TLS in place.
• If you migrate to production, consider containerizing the server and using a reverse proxy for TLS termination.
• Refer to IDE or editor plugins for MCP protocol assistance; many tools can auto-generate request bodies from capability descriptions.
• You can extend the server by adding more tools and resources described by MCP specifications, then re-run or reload the server to pick up changes.