---
id: dbt-metricflow
version: "0.13.0"
license: Apache-2.0
license_treatment: permissive
maintenance: active
---

# dbt-metricflow — Execute commands against the MetricFlow semantic layer with dbt.

License: permissive · Maintenance: active · Downloads: 381.1K/mo

## What it is and what it does

dbt-metricflow is a bundled distribution of dbt-core and MetricFlow that solves the version-reconciliation problem when using both tools together. Rather than installing dbt-core, metricflow, and a dbt adapter separately and manually ensuring their dbt-semantic-interfaces dependencies align, you install dbt-metricflow once and get a pre-coordinated set of compatible versions. The package wraps both tools' functionality and exposes a unified CLI that can execute semantic layer commands.

The package is in Beta status and actively maintained. It depends on six runtime packages (click, dbt-core, halo, jinja2, metricflow, and update-checker) and runs on Python 3.10 through 3.13. Installation is straightforward via pip with no compiled dependencies, making it accessible to most development environments. The Apache-2.0 license permits unrestricted use.

Use it for:

- Install dbt and MetricFlow once without version conflicts by using dbt-metricflow[adapter] instead of reconciling separate packages.
- Execute MetricFlow semantic layer queries and metric definitions through dbt's CLI without managing cross-package compatibility.
- Build shared CLI logic that depends on both dbt-core and MetricFlow without duplicating dependencies across repositories.
- Simplify onboarding for teams adopting dbt's semantic layer by reducing setup complexity to a single package install.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Bundles dbt-core and MetricFlow with compatible versioning, allowing you to execute semantic layer commands through a single unified installation instead of managing separate packages.

Yes, if you need both dbt-core and MetricFlow together. The bundled versioning eliminates a real pain point—manually reconciling dbt-semantic-interfaces versions across three separate packages. The package is actively maintained, has low install friction, carries a permissive license, and has no known vulnerabilities. Install it as dbt-metricflow[adapter] to include your dbt adapter of choice.

## Install

pip install dbt-metricflow
uv add dbt-metricflow
poetry add dbt-metricflow

## Installing dbt-metricflow

Before you install: Low friction: pure Python wheel with six runtime dependencies (click, dbt-core, halo, jinja2, metricflow, update-checker). Active maintenance with a recent commit on 2026-08-13 and 1740 repository stars.

License in practice: Apache-2.0 permissive license allows commercial and private use with minimal restrictions; you may use, modify, and distribute this package freely provided you include the license notice.

Quickstart:

pip install dbt-metricflow

from dbt_metricflow import cli
# Execute MetricFlow commands through dbt-metricflow's unified interface

Requires Python 3.10 or later (supports 3.10, 3.11, 3.12, 3.13); dbt-core and metricflow dependencies must be compatible versions as managed by this package.

Verify before relying:

- Whether the package's versioning management fully eliminates dbt-semantic-interfaces version conflicts in practice.
- Specific adapter support and whether all common dbt adapters are available through the [adapter] extra.
- Performance characteristics when executing large metric queries through the bundled CLI.

## Package facts

- License: Apache-2.0 (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 381.1K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

dbt semantic layer, metricflow dbt integration, unified dbt metricflow install, dbt metrics execution, semantic layer cli, dbt adapter bundling, metric definition and query, semantic-layer, dbt-integration, metrics-framework

[View on SkillFed](https://skillfed.io/packages/dbt-metricflow) · [View on PyPI](https://pypi.org/project/dbt-metricflow/)