create-python-server

Provides a command-line interface using Click that prompts developers for project metadata (name, version, description) and orchestrates the entire project creation workflow. The CLI component acts as the entry point that collects user inputs, validates them, and coordinates downstream template rendering and package initialization. This zero-configuration approach eliminates manual boilerplate setup by automating project structure generation and dependency installation in a single command.

Implements a template system using Jinja2 that processes project templates stored in the package and renders them with user-provided metadata (project name, version, description). The template engine reads Jinja2 template files (e.g., server.py.jinja2), substitutes variables with user inputs, and writes the rendered output to the generated project directory. This approach enables consistent, customizable project structures while keeping templates maintainable and version-controlled within the tool itself.

Integrates with the UV Python package manager to initialize generated projects and manage MCP SDK dependencies. After scaffolding the project structure, the tool invokes UV to create a virtual environment, install the mcp SDK package, and generate a lock file (uv.lock) that pins exact dependency versions. This integration ensures generated projects have reproducible, isolated dependency environments without requiring developers to manually run pip or poetry commands.

Automatically detects and configures the Claude Desktop application to recognize and load the newly created MCP server. The tool checks for Claude Desktop installation, reads its configuration file, registers the new MCP server with appropriate entry points and environment variables, and updates the configuration to enable seamless integration. This capability eliminates manual configuration steps by automatically wiring the generated MCP server into Claude Desktop's MCP server registry.

Generates a fully functional MCP server implementation that includes boilerplate code for the three core MCP protocol components: resources (data accessible via custom URI schemes), prompts (templates combining data for model interactions), and tools (functions that allow models to manipulate server state). The generated server.py file includes the MCP SDK imports, server initialization, and stub implementations for each component type, allowing developers to immediately extend with custom logic. This approach provides a working foundation that implements the Model Context Protocol specification without requiring developers to understand the protocol details.

Generates a complete Python project structure following standard packaging conventions, including src/ layout, pyproject.toml configuration, README.md documentation, __init__.py package markers, and __main__.py entry points. The generated structure follows Python packaging best practices (PEP 517, PEP 518) and enables the project to be installable via pip or UV. This capability ensures generated projects are immediately compatible with Python tooling ecosystems and can be published to PyPI or used as local packages.