Open Data Access for AI and ML
mloda is an open-source data access layer that connects AI tools to data sources reliably. Describe what data you need - mloda delivers it.
| Repository | Description |
|---|---|
| mloda | Core Python library. Plugin-based, traceable, framework-agnostic data access for AI agents and ML pipelines. |
| mloda-registry | Community and enterprise plugins, registry tooling, and development guides. |
| mloda-plugin-template | Template for creating your own FeatureGroups, ComputeFrameworks, and Extenders. |
pip install mloda from mloda.user import PluginLoader, mloda PluginLoader.all() result = mloda.run_all( features=["customer_id", "income", "income__sum_aggr", "age__avg_aggr"], compute_frameworks=["PandasDataFrame"], api_data={"SampleData": { "customer_id": ["C001", "C002", "C003", "C004", "C005"], "age": [25, 35, 45, 30, 50], "income": [50000, 75000, 90000, 60000, 85000] }} )Why mloda?
- Declarative - AI agents describe data needs, mloda resolves execution
- Plugin-based - Compose transformations without orchestration code
- Traceable - Full lineage from results back to source data
- Framework-agnostic - Works with Pandas, Polars, Spark, and custom backends
- Private - Runs on your infrastructure, no data leaves your systems
Get Involved
- Browse community plugins in the https://github.com/mloda-ai/mloda-registry
- Create your own plugin using the https://github.com/mloda-ai/mloda-plugin-template
- Read the https://mloda.ai