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# Use a Python image with uv pre-installed
FROM ghcr.io/astral-sh/uv:python3.13-bookworm-slim
RUN apt update -y && \
apt install -y --no-install-recommends libcairo2 && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
RUN apt update -y && \
curl --proto '=https' --tlsv1.2 -fsSL https://deb.nodesource.com/setup_22.x | bash - && \
apt-get install -y --no-install-recommends nodejs npm && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
RUN apt update -y && \
apt install -y --no-install-recommends curl gnupg2 iputils-ping jq less libxml2-utils nano procps psmisc && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
RUN npm install --ignore-scripts -g @modelcontextprotocol/[email protected]
# Install the project into `/app`
WORKDIR /app
# Enable bytecode compilation
ENV UV_COMPILE_BYTECODE=1
# Copy from the cache instead of linking since it's a mounted volume
ENV UV_LINK_MODE=copy
# Place executables in the environment at the front of the path
ENV PATH="/app/.venv/bin:$PATH"
# Install the project's dependencies using the lockfile and settings
RUN --mount=type=cache,target=/root/.cache/uv \
--mount=type=bind,source=uv.lock,target=uv.lock \
--mount=type=bind,source=pyproject.toml,target=pyproject.toml \
uv sync --frozen --no-install-project --no-dev --no-editable
# Then, add the rest of the project source code and install it
# Installing separately from its dependencies allows optimal layer caching
COPY pyproject.toml /app
COPY uv.lock /app
COPY src /app/src
COPY .env.example /app/.env.example
COPY tests /app/tests
COPY LICENSE /app
COPY *.md /app
COPY .python-version /app
RUN --mount=type=cache,target=/root/.cache/uv \
uv sync --frozen --no-dev --no-editable
# MCP Inspector
EXPOSE 5173/tcp
# MCP proxy server
EXPOSE 3000/tcp
ENV STARBRIDGE_RUNNING_IN_CONTAINER=1
# When running the container, start the Starbridge MCP server
# But feel free to add arguments and options as needed when doing a docker run
ENTRYPOINT ["uv", "run", "--no-dev", "starbridge"]