dbx-tools-graphiti

Native launcher for Graphiti with local Neo4j and LiteLLM processes configured for Databricks Model Serving. It runs directly on the host without Docker, Podman, or another container runtime.

Install from PyPI:

uv add dbx-tools-graphiti

Or install the current main branch:

uv add "dbx-tools-graphiti @ git+https://github.com/reggie-db/dbx-tools.git@main#subdirectory=packages/py/graphiti"

Key features

• launches upstream Graphiti’s HTTP MCP server at http://127.0.0.1:8000/mcp/;
• runs Neo4j Community 5.26 as a native background process;
• starts dbx-tools-litellm and authenticates through a Databricks CLI profile;
• defaults to databricks-gpt-5-nano and the 1024-dimensional databricks-gte-large-en embedding model;
• provisions Java 21 and uv through mise use -g only when absent;
• pins Graphiti and Neo4j versions for repeatable local environments;
• caches downloads, Python dependencies, Neo4j data, credentials, and logs;
• needs no config.yaml and does not vendor Graphiti code.

Quick start

mise and a working Databricks CLI profile must already be configured. The launcher handles Java, uv, LiteLLM, Graphiti, and Neo4j:

uv run dbx-graphiti start

The launcher uses DATABRICKS_CONFIG_PROFILE when set. Otherwise it runs databricks auth profiles --output json --skip-validate and uses the one entry marked "default": true. --profile <name> is an optional override, not a requirement.

The first run downloads about 120 MB of Neo4j plus the pinned Graphiti release, creates Graphiti’s uv environment, generates a local Neo4j password, starts LiteLLM and Neo4j, and then runs Graphiti in the foreground. Later runs reuse the installed assets.

For background operation:

uv run dbx-graphiti up
uv run dbx-graphiti status
uv run dbx-graphiti down

Commands

• setup provisions tools and populates the local cache without starting services.
• start starts Neo4j and LiteLLM, then runs Graphiti in the foreground. This is the default.
• up starts all three services in the background.
• down stops the managed Graphiti, LiteLLM, and Neo4j processes.
• status prints process state, model selection, and the MCP URL as JSON.
• env prints resolved database, proxy, and model settings as JSON. Its output includes the Neo4j password and must be treated as secret.

Arguments after -- are forwarded to upstream Graphiti:

uv run dbx-graphiti start -- --port 9000 --group-id my-agent

Provisioning and caching

The package deliberately keeps orchestration separate from Graphiti itself:

1. It checks mise where java@21 and mise where uv@0.11.
2. A missing tool is installed globally with mise use -g --yes.
3. Neo4j Community 5.26.12 is downloaded from dist.neo4j.org and unpacked.
4. Graphiti v0.29.3 is downloaded from its GitHub release tag.
5. uv sync --project <checkout>/mcp_server creates the upstream environment.
6. A generated Neo4j password is stored with mode 0600.
7. The packaged LiteLLM proxy starts against the selected Databricks profile, and Graphiti receives its OpenAI-compatible URL and model settings through environment variables and CLI flags.

The cache root is:

• macOS: ~/Library/Application Support/dbx-tools/graphiti
• Linux: ${XDG_DATA_HOME:-~/.local/share}/dbx-tools/graphiti
• Windows: %LOCALAPPDATA%/dbx-tools/graphiti

Set DBX_GRAPHITI_HOME to override it. Removing the directory clears the download cache and permanently removes the local graph data.

Configuration

There is no Graphiti config.yaml. Model and server settings resolve from CLI option, environment variable, then package default:

• --profile / DATABRICKS_CONFIG_PROFILE: an optional Databricks profile override for managed LiteLLM. When both are absent, the launcher uses the Databricks CLI profile marked as default.
• --model / MODEL_NAME: defaults to dbx/databricks-gpt-5-nano.
• --embedder-model / EMBEDDER_MODEL: defaults to dbx/databricks-gte-large-en.
• --embedder-dimensions / EMBEDDER_DIMENSIONS: defaults to 1024.
• --litellm-host / LITELLM_HOST: defaults to 127.0.0.1.
• --litellm-port / LITELLM_PORT: defaults to 4000.
• GRAPHITI_GROUP_ID: defaults upstream to main.
• GRAPHITI_HOST and GRAPHITI_PORT: default upstream to 127.0.0.1 and 8000.
• NEO4J_URI and NEO4J_DATABASE: default to bolt://127.0.0.1:7687 and neo4j.

The launcher sets Graphiti’s OpenAI provider and embedding dimensions directly. No OpenAI key is required for its managed local proxy.

To use a separately managed LiteLLM instance:

uv run dbx-graphiti start \
  --litellm-url https://models.example/v1 \
  --no-manage-litellm

Setting LITELLM_URL also selects external mode automatically. A direct OPENAI_API_URL selects external OpenAI-compatible mode and requires OPENAI_API_KEY. --manage-litellm overrides either environment choice when the launcher should still own the local proxy.

Explicit NEO4J_* values override generated defaults, which lets the Graphiti process use an existing Neo4j server. The launcher still manages its local Neo4j process; use upstream Graphiti directly if lifecycle ownership belongs to an external database administrator.

Graphiti owns MCP tools, graph behavior, LLM calls, embeddings, and migrations. This package owns repeatable installation, Databricks defaults, and process lifecycle. See the upstream MCP server documentation for its complete API.