metaxy

npx skills add majiayu000/claude-skill-registry --skill metaxy-anam-org-metaxy --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

# Metaxy Metaxy is a metadata layer for multimodal Data and ML pipelines that manages and tracks feature versions, dependencies, and data lineage across complex computational graphs. ## Core Concepts ### Feature Definitions To define a feature, create a class inheriting from `mx.BaseFeature` with a `FeatureSpec` metaclass argument: ```python import metaxy as mx class Video( mx.BaseFeature, spec=mx.FeatureSpec( key="media/video", id_columns=["video_id"], fields=["audio", "frames"], # Logical fields: describe data contents for versioning ), ): # Metadata columns: stored in the metadata store, tracked by metaxy video_id: str path: str duration: float height: int width: int ``` **Important distinction**: `fields` in `FeatureSpec` are logical field specs that describe the data contents for versioning and lineage tracking. Class attributes are metadata columns stored in the metadata store. They serve different purposes and should not overlap. To add dependencies between features, use the `deps` parameter with `FeatureDep`. To specify field-level lineage (for partial data dependencies), use `FieldSpec` with `FieldDep` or `FieldsMapping`. ### Data Versioning Metaxy automatically tracks sam

mx graph render            # Terminal visualization
mx push --store dev        # Push graph to store
mx list features --verbose     # List features with dependencies
mx graph render                # Visualize feature graph
mx metadata status --all-features  # Check metadata freshness (expensive!)
mx mcp                         # Start MCP server for AI assistants