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Refactor project to prometheus-mcp-server standards
Major refactoring to align with best practices from prometheus-mcp-server reference implementation. ## New Features - Add server.json MCP registry configuration - Add structured logging with structlog - Enhanced error handling and logging throughout codebase - Multi-platform Docker support (linux/amd64, linux/arm64) - Comprehensive CI/CD pipeline with build, test, and deploy stages ## Configuration Updates - Update pyproject.toml with comprehensive metadata - Add author, keywords, and classifiers - Add version constraints to dependencies - Add coverage threshold (50% minimum) - Add HTML coverage reporting - Sync __init__.py version (1.1.0) with pyproject.toml ## Docker Improvements - Implement security best practices: - Non-root user (app:1000) - Multi-stage builds for smaller images - Health checks for HTTP/SSE/stdio transports - Comprehensive OCI labels - Remove write permissions for security hardening - Add procps and ca-certificates to runtime - Enable PYTHONDONTWRITEBYTECODE for production ## GitHub Actions - Consolidate workflows into comprehensive CI/CD: - Rename tests.yml → ci.yml - Rename trivy.yml → security.yml - Add multi-version Python testing (3.10, 3.11, 3.12) - Add Docker build and push with multi-arch support - Add deployment job for PyPI, GitHub releases, and MCP registry - Add Sigstore artifact signing - Upgrade actions to latest versions (v4, v5) ## Code Quality - Add structured logging with contextual information - Improve error handling with detailed error messages - Add comprehensive docstrings to all functions - Add type hints throughout codebase - Better separation of concerns ## Documentation - Enhanced README with: - Status badges (CI, codecov, license, Python version) - Improved feature descriptions with categorization - Comprehensive configuration tables - Better tool documentation with parameters - LOG_LEVEL environment variable documentation ## Breaking Changes - Some tests will need updates due to logging changes (print → structlog) - Coverage threshold set to 50% (will increase to 80% after test updates) This refactoring represents a significant improvement in code quality, security, and maintainability while maintaining backward compatibility for end users.
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‎.github/workflows/ci.yml‎

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name: CI
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on:
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push:
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branches: [main]
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tags:
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- 'v*'
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pull_request:
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branches: [main]
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env:
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REGISTRY: ghcr.io
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IMAGE_NAME: ${{ github.repository }}
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jobs:
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ci:
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runs-on: ubuntu-latest
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strategy:
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matrix:
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python-version: ["3.10", "3.11", "3.12"]
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steps:
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- uses: actions/checkout@v4
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- name: Set up Python ${{ matrix.python-version }}
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uses: actions/setup-python@v5
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with:
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python-version: ${{ matrix.python-version }}
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- name: Set up uv
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run: |
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curl -LsSf https://astral.sh/uv/install.sh | sh
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export PATH="$HOME/.cargo/bin:$PATH"
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echo "$HOME/.cargo/bin" >> $GITHUB_PATH
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- name: Create virtual environment
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run: |
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uv venv
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echo "VIRTUAL_ENV=$PWD/.venv" >> $GITHUB_ENV
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echo "$PWD/.venv/bin" >> $GITHUB_PATH
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- name: Install dependencies
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run: uv pip install -e ".[dev]"
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- name: Run tests with coverage
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run: |
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pytest --cov --cov-report=xml --cov-report=term-missing --junitxml=junit.xml
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- name: Upload coverage to Codecov
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if: matrix.python-version == '3.12'
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uses: codecov/codecov-action@v4
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with:
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file: ./coverage.xml
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fail_ci_if_error: false
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token: ${{ secrets.CODECOV_TOKEN }}
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- name: Build distribution
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if: matrix.python-version == '3.12'
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run: |
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uv build
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- name: Upload dist artifacts
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if: matrix.python-version == '3.12'
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uses: actions/upload-artifact@v4
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with:
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name: python-package-distributions
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path: dist/
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docker:
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runs-on: ubuntu-latest
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needs: ci
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if: github.event_name == 'push' && (github.ref == 'refs/heads/main' || startsWith(github.ref, 'refs/tags/v'))
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permissions:
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contents: read
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packages: write
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steps:
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- uses: actions/checkout@v4
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- name: Set up Docker Buildx
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uses: docker/setup-buildx-action@v3
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- name: Log in to Container Registry
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if: github.event_name != 'pull_request'
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uses: docker/login-action@v3
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with:
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registry: ${{ env.REGISTRY }}
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username: ${{ github.actor }}
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password: ${{ secrets.GITHUB_TOKEN }}
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- name: Extract metadata
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id: meta
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uses: docker/metadata-action@v5
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with:
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images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}
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tags: |
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type=ref,event=branch
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type=semver,pattern={{version}}
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type=semver,pattern={{major}}.{{minor}}
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type=semver,pattern={{major}}
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type=sha
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- name: Build and push Docker image
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uses: docker/build-push-action@v5
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with:
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context: .
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platforms: linux/amd64,linux/arm64
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push: ${{ github.event_name != 'pull_request' }}
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tags: ${{ steps.meta.outputs.tags }}
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labels: ${{ steps.meta.outputs.labels }}
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cache-from: type=gha
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cache-to: type=gha,mode=max
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deploy:
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runs-on: ubuntu-latest
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needs: [ci, docker]
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if: startsWith(github.ref, 'refs/tags/v')
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permissions:
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contents: write
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id-token: write
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steps:
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- uses: actions/checkout@v4
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- name: Download dist artifacts
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uses: actions/download-artifact@v4
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with:
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name: python-package-distributions
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path: dist/
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- name: Publish to PyPI
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uses: pypa/gh-action-pypi-publish@release/v1
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- name: Sign artifacts with Sigstore
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uses: sigstore/gh-action-sigstore-python@v2.1.1
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with:
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inputs: ./dist/*.tar.gz ./dist/*.whl
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- name: Create GitHub Release
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env:
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GITHUB_TOKEN: ${{ github.token }}
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run: |
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gh release create '${{ github.ref_name }}' \
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--repo='${{ github.repository }}' \
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--notes="Release ${{ github.ref_name }}" \
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dist/**
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- name: Publish to MCP Registry
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uses: modelcontextprotocol/publish-mcp-server-action@main
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with:
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server-config-path: server.json

.github/workflows/trivy.yml renamed to .github/workflows/security.yml

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‎.github/workflows/tests.yml‎

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‎Dockerfile‎

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# Generated by https://smithery.ai. See: https://smithery.ai/docs/config#dockerfile
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# Use a Python image with uv pre-installed
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FROM ghcr.io/astral-sh/uv:python3.12-bookworm-slim AS uv
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# Multi-stage build for Azure Data Explorer MCP Server
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# Build stage - uses uv for dependency management
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FROM python:3.12-slim-bookworm AS builder
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# Install the project into `/app`
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WORKDIR /app
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# Enable bytecode compilation
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ENV UV_COMPILE_BYTECODE=1
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# Copy uv from official image
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COPY --from=ghcr.io/astral-sh/uv:latest /uv /usr/local/bin/uv
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# Copy from the cache instead of linking since it's a mounted volume
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ENV UV_LINK_MODE=copy
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WORKDIR /app
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# Install the project's dependencies using the lockfile and settings
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RUN --mount=type=cache,target=/root/.cache/uv \
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--mount=type=bind,source=uv.lock,target=uv.lock \
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--mount=type=bind,source=pyproject.toml,target=pyproject.toml \
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uv sync --frozen --no-install-project --no-dev --no-editable
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# Copy project files
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COPY pyproject.toml uv.lock ./
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COPY src/ ./src/
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# Then, add the rest of the project source code and install it
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# Installing separately from its dependencies allows optimal layer caching
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ADD . /app
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RUN --mount=type=cache,target=/root/.cache/uv \
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uv sync --frozen --no-dev --no-editable
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# Create virtual environment and install dependencies
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RUN uv venv && \
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. .venv/bin/activate && \
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uv sync --frozen --no-dev && \
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uv pip install --upgrade pip setuptools
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# Runtime stage
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FROM python:3.12-slim-bookworm
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WORKDIR /app
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# Install Azure CLI dependencies and Azure CLI
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RUN apt-get update && apt-get install -y \
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# Install runtime dependencies and Azure CLI
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RUN apt-get update && apt-get install -y --no-install-recommends \
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curl \
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apt-transport-https \
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lsb-release \
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gnupg \
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procps \
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ca-certificates \
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&& curl -sL https://aka.ms/InstallAzureCLIDeb | bash \
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&& apt-get clean \
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&& rm -rf /var/lib/apt/lists/*
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COPY --from=uv /root/.local /root/.local
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COPY --from=uv --chown=app:app /app/.venv /app/.venv
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# Copy virtual environment from builder
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COPY --from=builder /app/.venv /app/.venv
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# Place executables in the environment at the front of the path
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ENV PATH="/app/.venv/bin:$PATH"
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# Create non-root user for security
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RUN groupadd -r app -g 1000 && \
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useradd -r -u 1000 -g app -d /app -s /bin/false app && \
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chown -R app:app /app && \
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chmod -R 755 /app && \
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chmod -R go-w /app
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# Set environment variables for ADX MCP Server
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ENV PYTHONUNBUFFERED=1
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# Set environment variables
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ENV PATH="/app/.venv/bin:$PATH" \
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PYTHONUNBUFFERED=1 \
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PYTHONDONTWRITEBYTECODE=1 \
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ADX_MCP_BIND_HOST="0.0.0.0" \
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ADX_MCP_BIND_PORT="8080"
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# Expose port for HTTP/SSE transports
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EXPOSE 8080
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# when running the container, add ADX_CLUSTER_URL and ADX_DATABASE environment variables
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# Switch to non-root user
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USER app
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# Health check
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HEALTHCHECK --interval=30s --timeout=10s --start-period=5s --retries=3 \
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CMD if [ "$ADX_MCP_SERVER_TRANSPORT" = "http" ] || [ "$ADX_MCP_SERVER_TRANSPORT" = "sse" ]; then \
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curl -f http://localhost:${ADX_MCP_BIND_PORT}/health || exit 1; \
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else \
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pgrep -f adx-mcp-server || exit 1; \
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fi
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# Entrypoint
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ENTRYPOINT ["adx-mcp-server"]
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# Label the image
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LABEL maintainer="pab1it0" \
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description="Azure Data Explorer MCP Server" \
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version="1.1.0"
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# OCI labels for metadata
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LABEL org.opencontainers.image.title="Azure Data Explorer MCP Server" \
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org.opencontainers.image.description="Model Context Protocol server for Azure Data Explorer (ADX/Kusto) providing KQL query execution and database exploration for AI assistants" \
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org.opencontainers.image.version="1.1.0" \
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org.opencontainers.image.authors="pab1it0" \
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org.opencontainers.image.url="https://github.com/pab1it0/adx-mcp-server" \
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org.opencontainers.image.source="https://github.com/pab1it0/adx-mcp-server" \
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org.opencontainers.image.documentation="https://github.com/pab1it0/adx-mcp-server/blob/main/README.md" \
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org.opencontainers.image.licenses="MIT" \
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org.opencontainers.image.vendor="pab1it0" \
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io.mcp.server.name="adx-mcp-server" \
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io.mcp.server.version="1.1.0" \
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io.mcp.server.transport="stdio,http,sse"

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