Dataproc MCP Server

# Dataproc MCP Server Development Guide ## Build & Test Commands ### Using uv (recommended) - Install dependencies: `uv pip install --system -e .` - Install dev dependencies: `uv pip install --system -e ".[dev]"` - Update lock file: `uv pip compile --system pyproject.toml -o uv.lock` - Install from lock file: `uv pip sync --system uv.lock` ### Using pip (alternative) - Install dependencies: `pip install -e .` - Install dev dependencies: `pip install -e ".[dev]"` ### Running the server - Run server (stdio): `python -m dataproc_mcp_server` - Run server with HTTP transport: `DATAPROC_MCP_TRANSPORT=http python -m dataproc_mcp_server` - Run server with SSE transport: `DATAPROC_MCP_TRANSPORT=sse python -m dataproc_mcp_server` - Run with MCP CLI: `mcp run src/dataproc_mcp_server/server.py` - Run with debug logging: `DATAPROC_MCP_DEBUG=true python -m dataproc_mcp_server` ### Transport Configuration - **STDIO** (default): Standard input/output communication for command-line tools - **HTTP**: REST API over HTTP using streamable-http transport - **SSE**: Server-Sent Events for real-time communication - Set host/port: `DATAPROC_MCP_HOST=0.0.0.0 DATAPROC_MCP_PORT=8080` ### Testing and linting - Run tests: `pytest` - Run single test: `pytest tests/path/to/test_file.py::test_function_name -v` - Run tests with coverage: `python -m pytest --cov=src/dataproc_mcp_server tests/` - Run linter: `ruff check src/ tests/` - Format code: `ruff format src/ tests/` ## Technical Stack - **Python version**: Python 3.13+ - **Project config**: `pyproject.toml` for configuration and dependency management - **Environment**: Use virtual environment in `.venv` for dependency isolation - **Package management**: Use `uv` for faster, more reliable dependency management with lock file - **Dependencies**: Separate production and dev dependencies in `pyproject.toml` - **Version management**: Use `setuptools_scm` for automatic versioning from Git tags - **Linting**: `ruff` for style and error checking - **Type checking**: Use VS Code with Pylance for static type checking - **Project layout**: Organize code with `src/` layout ## Code Style Guidelines - **Formatting**: Black-compatible formatting via `ruff format` - **Imports**: Sort imports with `ruff` (stdlib, third-party, local)