dbt CLI MCP Server

# Environment Setup Guide for MCP Servers ## Overview This guide covers how to set up the development environment for Model Context Protocol (MCP) servers in Python using uv for dependency management. ## Installing uv `uv` is a fast Python package installer and environment manager. To install it: ```bash # Install uv curl -LsSf https://astral.sh/uv/install.sh | sh # Verify installation uv --version ``` ## Initial Project Structure Create a new directory for your MCP server project: ```bash mkdir my-mcp-server cd my-mcp-server ``` ## Setting Up Testing Environment Create a proper pytest configuration to ensure tests work correctly with uv: 1. Create a `pytest.ini` file in the project root: ```ini [pytest] testpaths = tests python_files = test_*.py python_classes = Test* python_functions = test_* # Log format log_cli = true log_cli_level = INFO log_cli_format = %(asctime)s [%(levelname)8s] %(message)s (%(filename)s:%(lineno)s) log_cli_date_format = %Y-%m-%d %H:%M:%S # Test selection options addopts = --strict-markers -v ``` 2. Create a `tests/__init__.py` file to make the tests directory a package: ```python # tests/__init__.py # This file makes the tests directory a package ``` 3. Create a `tests/conftest.py` file for shared fixtures: ```python # tests/conftest.py import os import sys import pytest import logging # Add parent directory to path to allow imports from the main package sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..'))) # Configure test logger logging.basicConfig( level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s', datefmt='%Y-%m-%d %H:%M:%S' ) logger = logging.getLogger("test_logger") # Define fixtures that can be used across tests @pytest.fixture def test_fixtures_dir(): """Return the path to the test fixtures directory.""" return os.path.join(os.path.dirname(__file__), 'fixtures') ``` ## Running Your MCP Server ### With Environment Variables For environment variables, create a `.env` file: ``` API_KEY=your_api_key_here DEBUG_MODE=true ``` Then run with the `--env-file` option: ```bash uv run my_mcp_server.py --env-file .env ``` Or export environment variables directly: ```bash export API_KEY=your_api_key_here uv run my_mcp_server.py ``` ## Next Steps After setting up your environment, refer to: - [Project Structure Guide](project_structure_guide.md) for required project organization - [Dependency Guide](dependency_guide.md) for dependency management with uv - [Implementation Guide](implementation_guide.md) for MCP server implementation patterns