Pbix Atlas MCP server

🌐 PBIX‑Atlas

Full lineage graph for Power BI — from source to visual field

<!-- mcp-name: io.github.fabienfrfr/pbix-atlas -->

PbixAtlas is an Universal lineage graph for Power BI .pbix files: source to visual field in one traversable graph.

source (HTTP, OData, SQL, file...) --> Power Query (M)
    --> column / calculated column --> measure (DAX)
        --> field displayed in a report visual

Install

pip install pbix-atlas
# or
uv add pbix-atlas

Quick start

from pbix_atlas import LineageGraphBuilder, upstream, downstream, print_tree, find_nodes

graph = LineageGraphBuilder().build("my_report.pbix")

find_nodes(graph, "customer_name")
print_tree(graph, "visual_field::my_report.pbix::Page1::16::customer_name", direction="upstream")
print_tree(graph, "source::odata::example.com/odata/", direction="downstream")

Export

from pbix_atlas import export_graphml, export_nodes_csv, export_edges_csv, graph_summary

graph_summary(graph)  # {'query': 70, 'column': 183, ...}
export_graphml(graph, "lineage.graphml")  # Gephi / yEd
export_nodes_csv(graph, "nodes.csv")
export_edges_csv(graph, "edges.csv")

Codegen — standalone Python pipeline

Generates a single Python file reproducing a report's full chain: source → extraction → Power Query → semantic model → Vizro dashboard. The M source is executed at runtime by the built-in interpreter, not pattern-matched. Unimplemented functions raise MRuntimeError (no silent stubs).

pip install "pbix-atlas[codegen]"
pbix-atlas-codegen my_report.pbix -o pipeline.py

from pbix_atlas import generate_python_pipeline

generate_python_pipeline("my_report.pbix", "pipeline.py")

HTTP API / MCP server

uv sync --extra api
uv run pbix-atlas    # http://127.0.0.1:8080

• REST: POST /graphs, /search, /upstream, /downstream, /tree, /export, /codegen
• MCP (streamable HTTP): http://127.0.0.1:8080/mcp/
• Env vars: PBIXLINEAGEHOST, PBIXLINEAGEPORT

Architecture

Sample files

• Retail Analysis Sample PBIX (Microsoft)
• Sales & Returns Sample v201912 (Microsoft)

Development

Shortened. The full README is on GitHub.