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MCP Server for Splunk

Dockerfileβ€’1.6 kB
# Use Python 3.11 slim image for smaller size FROM python:3.11-slim # Set working directory WORKDIR /app # Set environment variables ENV PYTHONUNBUFFERED=1 ENV PYTHONDONTWRITEBYTECODE=1 ENV MCP_SERVER_MODE=docker ENV PYTHONPATH=/app # Install system dependencies and uv (via official installer) RUN apt-get update && apt-get install -y --no-install-recommends \ curl \ ca-certificates \ && rm -rf /var/lib/apt/lists/* # Download and install uv ADD https://astral.sh/uv/install.sh /uv-installer.sh ENV UV_INSTALL_DIR=/usr/local/bin RUN sh /uv-installer.sh && rm /uv-installer.sh # Ensure uv is on PATH ENV PATH="${PATH}:/root/.cargo/bin" # Copy dependency files first for better caching COPY pyproject.toml uv.lock README.md ./ COPY LICENSE ./ # Install Python dependencies using uv (include watchdog and reload tools for hot reload) RUN uv sync --frozen --no-dev && uv add watchdog reloader # Copy source code COPY src/ ./src/ COPY contrib/ ./contrib/ COPY docs/ ./docs/ # Create logs directory RUN mkdir -p /app/src/logs # Expose the internal HTTP port the server binds to EXPOSE 8001 # Run the MCP server using uv with enhanced hot reload support CMD ["sh", "-c", "echo 'Starting modular MCP server (src/server.py)'; if [ \"$MCP_HOT_RELOAD\" = \"true\" ]; then echo 'Starting with enhanced hot reload...'; uv run watchmedo auto-restart --directory=./src --directory=./contrib --pattern=*.py --recursive --ignore-patterns='*/__pycache__/*;*.pyc;*.pyo;*/.pytest_cache/*' -- python -u src/server.py; else echo 'Starting in production mode...'; uv run python src/server.py; fi"]

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