generated: '2026-07-18'
method: searched
source: https://bruin-data.github.io/bruin/
description: >-
  Bruin ships a first-party, Git-native CLI (Apache-2.0, Go) that is the primary
  way to build and run data pipelines - SQL and Python assets, ingestion,
  quality checks, lineage, and Bruin Cloud operations. A companion CLI, ingestr,
  copies data between 100+ sources and destinations.
clis:
  - name: bruin
    binary: bruin
    repo: https://github.com/bruin-data/bruin
    docs: https://bruin-data.github.io/bruin/
    license: Apache-2.0
    install:
      - method: curl
        command: curl -LsSf https://getbruin.com/install/cli | sh
      - method: wget
        command: wget -qO- https://getbruin.com/install/cli | sh
      - method: homebrew
        command: brew install bruin-data/tap/bruin
        note: deprecated
    commands:
      - name: init
        summary: Scaffold a new pipeline project from a template.
      - name: run
        summary: Execute a pipeline or an individual asset.
      - name: validate
        summary: Check pipeline and asset configuration validity.
      - name: unit-test
        summary: Run data/unit tests for assets.
      - name: query
        summary: Execute a query against a configured connection.
      - name: lineage
        summary: Visualize column- and asset-level dependencies.
      - name: data-diff
        summary: Compare tables across connections/environments.
      - name: render
        summary: Render an asset's compiled SQL/query.
      - name: format
        summary: Format pipeline/asset files.
      - name: import
        summary: Import assets/definitions into a project.
      - name: patch
        summary: Apply patches to assets.
      - name: clean
        summary: Clean generated/temporary artifacts.
      - name: connections
        summary: Manage data connections.
      - name: environments
        summary: Manage pipeline environments.
      - name: mcp
        summary: Start the Bruin MCP server (stdio) for AI assistants.
      - name: ai skills
        summary: Install or update packaged agent skills for a repository.
      - name: ai enhance
        summary: AI-assisted enhancement of assets/pipelines.
      - name: cloud
        summary: Bruin Cloud operations (scheduled-runs, dashboards, deploy).
    key_flows:
      - Scaffold and run a first pipeline (init -> run).
      - Ingest from an external source, transform with SQL/Python, add quality checks.
      - Diff data across environments before promotion (data-diff).
      - Serve the CLI as an MCP server for AI agents (bruin mcp).
  - name: ingestr
    binary: ingestr
    repo: https://github.com/bruin-data/ingestr
    docs: https://bruin-data.github.io/ingestr/
    license: MIT
    install:
      - method: pip
        command: pip install ingestr
    summary: >-
      Copy data from any source to any destination with a single command;
      supports append, merge, and delete+insert incremental strategies across
      100+ sources and destinations.