MCP synthetic data server

Optional local MCP server

The MCP server is a local stdio wrapper over existing public APIs. It does not introduce a separate generation engine.

Great Generator creates synthetic data. It does not anonymize, mask, de-identify, or transform production records.

Getting started API reference GitHub

Install and start

MCP dependencies are optional and are not part of the base install.

pip install "great-generator[mcp]"

great-generator-mcp

Output behavior

MCP tools write generated data to local files and return row counts, paths, schema summaries, warnings, previews, and manifest paths instead of returning large datasets in chat.

Safety defaults

The server enforces local path checks, row limits, and overwrite protection. It does not write to production systems.

Related documentation

Keep exploring

Installation optionsInstall Great Generator for core Pandas workflows, Spark, Delta Lake, optional AI advisors, or the optional local MCP server. Generate synthetic data from schemasCreate synthetic test data from schema strings, dictionaries, Pandas DataFrames, and Spark schemas using semantic field detection. Relational synthetic dataGenerate related synthetic tables with primary-key and foreign-key behavior for joins, warehouse models, tests, demos, and analytics examples. API reference overviewReview the main Great Generator public APIs for schema generation, SQL DDL parsing, relational generation, CDC, anomalies, advisors, and exports. GitHub repositorySource code, issues, releases, and project history. PyPI packageInstall Great Generator from Python Package Index.