fabric-dw

Python CLI and MCP server for Microsoft Fabric Data Warehouses and SQL Analytics Endpoints: administer, query, optimize, and secure them from your terminal or your AI agent.

Full documentation: fdw.debruyn.dev

📣 Just announced! Read the story behind fabric-dw in the announcement blog post.

Description

fabric-dw provides two interfaces for managing Microsoft Fabric Data Warehouses and SQL Analytics Endpoints:

• CLI: a command-line tool for common DW administration tasks.
• MCP server: a Model Context Protocol server that exposes DW operations as tools for AI assistants.

Authentication is configured via the FABRIC_AUTH environment variable. The default (FABRIC_AUTH=default) uses azure-identity DefaultAzureCredential, which walks environment variables, Workload/Managed Identity, Azure CLI, Azure Developer CLI, Azure PowerShell, and interactive browser in order. Any of these will satisfy it. See the Authentication docs for the full chain, all supported sources, and debugging tips.

Installation

pip install fabric-dw
# or run without installing:
uvx fabric-dw --help
# or install persistently on PATH:
uv tool install fabric-dw

After installation, the fdw command is a short alias for fabric-dw; both invoke the same entry point. See the Install docs for MCP server setup, upgrading, and prerelease builds.

Quick Start

CLI

The workspace is a global root option -w / --workspace placed before the command group. Set a default once with fdw config set workspace <NAME> and omit -w on every subsequent call. Workspace resolution order: (1) -w flag, (2) FABRIC_DW_DEFAULT_WORKSPACE env var, (3) configured default.

# Run without installing; install to get the fdw alias
uvx fabric-dw --help

# Set a default workspace once; all subsequent commands pick it up
fdw config set workspace SalesWS

# -- Run and explain SQL --

# Execute a query against a warehouse
fdw sql exec SalesWH -q "SELECT TOP 10 * FROM dbo.orders ORDER BY order_date DESC"

# Capture an estimated execution plan as SVG -- no SSMS or Windows needed
fdw sql plan SalesWH -f query.sql --format svg -o plan.svg

# -- Performance mission-control --

# See what is running right now
fdw queries running SalesWH

# Long-running queries from the past hour
fdw queries long-running SalesWH --ago 1h

# Kill a runaway session by ID
fdw queries kill SalesWH 55

# Most-repeated queries over the past 24 hours
fdw queries frequent SalesWH --ago 24h

# -- Optimize --

# Inspect a statistics histogram with inline terminal bar charts
fdw statistics show SalesWH dbo.orders st_order_date --histogram

# Re-cluster a table on a new key (transactional CTAS-swap, auto-rollback on failure)
fdw tables cluster-by SalesWH dbo.orders --cluster-by customer_id

# -- Time travel + export --

# Browse the table as it looked 2 hours ago
fdw tables read SalesWH dbo.orders --ago 2h

# Export a point-in-time snapshot to Parquet
fdw tables export SalesWH dbo.orders --output snapshot.parquet --ago 2h

# -- Governance --

# Grant SELECT on a specific table
fdw permissions sql grant SalesWH SELECT --to analyst@company.com --object dbo.orders

# Deny access to sensitive columns (column-level security)
fdw permissions cls deny SalesWH SELECT --to contractor@company.com \
    --object dbo.orders --columns salary,bonus

# Create a row-level security policy (filter rows by SalesRep)
fdw permissions rls create SalesWH rls.SalesFilter \
    --filter "rls.fn_sales_filter(SalesRep)" --on dbo.orders

# -- Load + scaffold --

# Load a local Parquet file and auto-create the table from its schema
fdw tables load SalesWH dbo.orders --file orders.parquet --create

# Scaffold a full dbt-fabric project wired to the warehouse
fdw dbt init SalesWH ./my-dbt-project --project-name sales_dw --with-sources

MCP Server

Add to your MCP client configuration (e.g. Claude Desktop, VS Code):

{
  "mcpServers": {
    "fabric-dw": {
      "command": "uvx",
      "args": ["--from", "fabric-dw", "fabric-dw-mcp"]
    }
  }
}

The MCP server exposes all CLI operations as MCP tools (workspaces, warehouses, SQL endpoints, schemas, tables, views, queries, snapshots, restore points, audit, statistics, permissions, sql-pools). Bundled Claude Code agent skills (query-optimizer, warehouse-performance, dbt-setup) are included for deeper AI-assisted analysis. Set FABRIC_AUTH in the environment if you need a non-default auth mode.

Both the skills and the MCP server install in one command via the fabric-dw plugin marketplace, for Claude Code and GitHub Copilot CLI alike: /plugin marketplace add sdebruyn/fabric-dw-mcp-cli then /plugin install fabric-dw@fabric-dw. See the Agent Skills docs for details.

Run in Docker

The Docker image's default ENTRYPOINT is the MCP server (fabric-dw-mcp). Use it as-is with your MCP client, or override the entrypoint to run the CLI instead.

docker pull ghcr.io/sdebruyn/fabric-dw:latest

# Run the MCP server (default entrypoint, connect via stdio from your MCP client):
docker run --rm -i \
  -e AZURE_CLIENT_ID=… \
  -e AZURE_TENANT_ID=… \
  -e AZURE_CLIENT_SECRET=… \
  -e FABRIC_AUTH=sp \
  ghcr.io/sdebruyn/fabric-dw

# Run the CLI instead (override the entrypoint):
docker run --rm \
  --entrypoint fabric-dw \
  -e AZURE_CLIENT_ID=… \
  -e AZURE_TENANT_ID=… \
  -e AZURE_CLIENT_SECRET=… \
  -e FABRIC_AUTH=sp \
  ghcr.io/sdebruyn/fabric-dw --help

Dev images (built from every main merge): ghcr.io/sdebruyn/fabric-dw:main or :<version>.dev<N>.

Package page: ghcr.io/sdebruyn/fabric-dw

Security environment variables

HTTP transport

The MCP server can be started in HTTP mode for remote clients:

fabric-dw-mcp --transport http [--host 127.0.0.1] [--port 8000]

It binds to loopback by default, where Host and Origin validation is handled for you. Binding anywhere else requires FABRIC_MCP_ALLOW_REMOTE=1 and --allowed-host, and the endpoint has no built-in authentication or TLS, so always front it with an authenticating reverse proxy. See Hosting the MCP server for that setup.

Develop in a container

Open the repo in GitHub Codespaces or VS Code's Remote-Containers extension. The devcontainer pre-installs Python 3.14, uv, Azure CLI, and the GitHub CLI.

Contributing

See CONTRIBUTING.md for dev setup, branch flow, and how to run tests locally.

📖 Docs: fdw.debruyn.dev (or run uv run --only-group docs zensical serve locally).

Security

Please report vulnerabilities privately. See SECURITY.md.

Code of Conduct

This project follows the Contributor Covenant 2.1.

License

MIT. Copyright (c) 2026 Sam Debruyn