Dockerfile

# Use a Python image with uv pre-installed
FROM ghcr.io/astral-sh/uv:python3.12-bookworm-slim AS uv

# 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

# 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
ADD . /app
RUN --mount=type=cache,target=/root/.cache/uv \
    uv sync --frozen --no-dev --no-editable

FROM python:3.12-slim-bookworm

WORKDIR /app
 
COPY --from=uv /root/.local /root/.local
COPY --from=uv --chown=app:app /app/.venv /app/.venv

# Place executables in the environment at the front of the path
ENV PATH="/app/.venv/bin:$PATH"

# Use default API URL (https://api.agentops.ai) - agents can override per-request
ENTRYPOINT ["python", "-m", "mcp_server_agentops_api"]