graphify Docker & Self-Hosted Deployment

GitHub

Turn any codebase, with its docs, SQL schemas, configs, and PDFs, into a queryable knowledge graph. A /graphify skill for Claude Code, Cursor, Codex, and...

105,718 stars Python Python 1 file · ~12,828 tokens #ai-agents#antigravity#ast#claude-code#code-analysis#code-search#codex#cursor
1. Pull Image (DOCKERHUB) docker pull Graphify-Labs/graphify:latest
2. Docker Run (1-Click Launch) docker run -d --name graphify -p 8080:8080 --restart always graphify-labs/graphify:latest
3. Podman Run podman run -d --name graphify -p 8080:8080 --restart always graphify-labs/graphify:latest
4. Skopeo Inspect (Zero-Pull Manifest) skopeo inspect docker://docker.io/graphify-labs/graphify:latest
5. ORAS Pull (OCI Artifact) oras pull graphify-labs/graphify:latest
Dockerfile 
# graphify MCP server as a shared HTTP service (issue #1143).
#
# Build:  docker build -t graphify .
# Run:    docker run -p 8080:8080 -v "$(pwd)/graphify-out:/data" graphify \
#             /data/graph.json --transport http --host 0.0.0.0 --api-key "$SECRET"
#
# Builds from source so the image includes the Streamable HTTP transport even
# before it lands on PyPI. The graph.json is mounted at runtime (-v), never
# baked into the image.
FROM python:3.12-slim

WORKDIR /app
COPY . /app

# The [mcp] extra pulls mcp + starlette + uvicorn, which the HTTP transport needs.
RUN pip install --no-cache-dir ".[mcp]"

# Run as a non-root user — the server is network-exposed.
RUN useradd --create-home --uid 10001 graphify
USER graphify

EXPOSE 8080

ENTRYPOINT ["python", "-m", "graphify.serve"]
CMD ["/data/graph.json", "--transport", "http", "--host", "0.0.0.0", "--port", "8080"]