Semantic Model Python Packages

horizun-pbi-mcp

Open-source Power BI MCP to build, audit and repair Desktop models and PBIP reports with DAX, TOM, TMDL and PBIR.

trailsbi

End-to-end data lineage, model health and AI readiness for Power BI. Offline. Free. Open Source.

fabric-ai-meta

Extract Microsoft Fabric semantic model metadata. AI-ready exports for LangChain, OpenAI, Semantic Kernel, AutoGen, and custom plugins. Multi-provider LLM enrichment, MCP server, and cross-model governance.

seshat-bi

Readiness system that lets AI agents build your BI pipeline but never approve it -- evidence-gated source profiling, medallion mappings, metric contracts, and Power BI delivery. Offline demo in 60 seconds: uvx --from seshat-bi seshat demo init

model-lenz

Find the lineage, understand the model, document both. Trace every Power BI column back to its physical source, read a model you did not build, and generate documentation that cannot go stale — or hand it over as one self-contained HTML file.

fabric-schema-drift-detective

Enterprise-grade schema drift detection for Microsoft Fabric with automated change detection, impact analysis, schema history, and DevOps integration.

pbi-docs

AI context engine for Power BI models — turns .pbit/.pbip (TMDL) into indexed, queryable context for LLM agents (MCP server, CLI, docs). Zero dependencies.

pbi-context

AI context engine for Power BI models — turns .pbit/.pbip (TMDL) into indexed, queryable context for LLM agents (MCP server, CLI, docs). Zero dependencies.

pbi2snow

Power BI to Snowflake SQL translator with enhanced M and DAX support