dbt-metricflow
Execute commands against the MetricFlow semantic layer with dbt.
Decision gist · record as of 2026-08-14
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.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- 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.
- 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 · maintenance · safety
Apache-2.0 (permissive) — 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.
last release 2026-05-12 (94 days) · last repo commit 2026-08-13 · 1,740 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 381,101 downloads/mo, #7,099 on PyPI
Alternatives
Verify before relying
pip install dbt-metricflow
from dbt_metricflow import cli
# Execute MetricFlow commands through dbt-metricflow's unified interface- 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.
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 on this page. Verify before relying on it.
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
dbt-metricflow on PyPI
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.
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.
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 interfaceVerify 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 the current Python release <3.14,>=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 6 packagesclickdbt-corehalojinja2metricflowupdate-checker |
| Maintenance | Actively maintained 94 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 381,101 / month, #7,099 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 4 - BetaProgramming Language :: PythonProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: Implementation :: CPythonProgramming Language :: Python :: Implementation :: PyPy |
Evidence: dbt_metricflow-0.13.0-py3-none-any.whl
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See also dbt-semantic-interfaces · metricflow · dbt-sl-sdk · dbt-common · cube_dbt · dbt-fabric · dbt-fusion-package-tools · dbt-sqlserver · dbt-adapters · spec-kitty-tracker