A smoother dbt workflow, without leaving VS Code — and without your SQL ever leaving your machine.

What is dbt Forge?

dbt Forge is a VS Code extension for data engineers working on dbt projects (built and tested against dbt-fabric / Microsoft Fabric, but not tied to it). It fills the gaps left by existing dbt tooling — column-level autocomplete, an interactive lineage graph, and one-click build shortcuts — while keeping everything 100% local.

Nothing is sent anywhere. No account, no API key, no third-party backend. dbt Forge only reads the files your own dbt already produces (manifest.json, catalog.json, compiled SQL) and runs dbt through your own project's Python environment.

Features

	Feature	Description
🔗	ref()/source() autocomplete	Suggests model, seed, snapshot and source names as you type inside `{{ ref('...` / `{{ source('...', '...`
⚡	Snippet expansion	Type `ref` or `source` in plain SQL to expand into the full `{{ ref("") }}` tag, cursor ready to autocomplete
🧭	Go to Definition	Ctrl+click a `ref()`/`source()`/macro call to jump straight to the file it resolves to — a model's or macro's `.sql`, a seed's `.csv`
🔍	Find All References	Shift+F12 (or right-click) on a model, source, or macro to list every call site across the project
💬	Hover documentation	Hover a `ref()`/`source()`/macro call to see its description (and a macro's argument signature) straight from the manifest
⚠️	Broken ref()/source() diagnostics	Warns in the Problems panel (and inline) when a `ref()`/`source()` call doesn't resolve against the manifest — e.g. a typo or a renamed/deleted model
🔤	Column autocomplete	Suggests column names after `alias.`, resolved from `catalog.json` (requires `dbt docs generate` — see below) and from same-file CTEs
🌳	Parents / Children / Tests panel	Sidebar view of the current model's direct dependencies and dependents, from the manifest's dependency graph
🕸️	Interactive lineage graph	Click-to-expand upstream/downstream graph (React Flow) — starts at the current model, seed or snapshot, no giant unreadable diagram dumped on you. Each node shows its materialization and wears the `node_color` your project declares
👁️	Compiled SQL preview	Read-only, side-by-side preview of the compiled SQL dbt actually runs
📊	Data preview	`Ctrl+Enter` on a model to run `dbt show` and read the rows in a Data Preview tab in the bottom panel — works on models that were never materialized, and on `ephemeral` ones
🧩	Per-CTE preview	A preview button on every CTE, to inspect an intermediate step without commenting out the rest of the query
🚀	Build / Test shortcuts	CodeLens and sidebar buttons for Build Upstream, Build Downstream, Test, and Build Project — run through your project's own venv
🔀	Environment switching	Status bar picker over the profiles in your `profiles.yml` — every dbt command dbt Forge runs then carries that `--profile`/`--target`, so a dev branch can point at a different Fabric workspace than main
📄	Compile This File	Compiles only the open model (`dbt compile --select path:<file>`) — the fast way to get a just-created model into the manifest, without a full-project compile
🏷️	Tags panel	Every tag declared in the project, expandable to its resources, with one-click Build / Build Upstream / Build Downstream / Test per tag

Getting Started

Prerequisites

VS Code 1.85+
A dbt project (dbt_project.yml) with its own Python virtual environment (dbt-core + your adapter installed inside it)
manifest.json generated at least once (dbt compile or dbt build) for autocomplete/lineage/panels to have data
catalog.json generated (dbt docs generate, or the Generate Docs button) for column autocomplete on already-built models

Installation

From the VS Code Marketplace — open the Extensions view (Ctrl+Shift+X), search for dbt Forge, and click Install. Or, from a terminal:

code --install-extension evolve-data.dbtforge

The extension is also on the Marketplace page, and activates on its own as soon as the folder you open contains a dbt_project.yml.

From a .vsix

(a release download, or your own build)

code --install-extension dbtforge-0.11.0.vsix

From source

(to hack on the extension)

git clone https://github.com/Y0hannH/dbtforge
cd dbtforge
npm install
npm run compile

Then press F5 in VS Code to launch an Extension Development Host with dbt Forge loaded, and open your dbt project in that window. npm test runs the unit suite; npx vsce package produces an installable .vsix.

First Run

Open your dbt project folder (containing dbt_project.yml, or nested inside a larger workspace)
Set dbtForge.pythonPath to your project's venv Python (e.g. C:/path/to/project/.venv/Scripts/python.exe)
Run dbt compile (or dbt build) at least once so manifest.json exists
Run dbt Forge: Generate Docs (the 📖 button in the panel's title bar) so catalog.json exists — column autocomplete needs it
Open a model .sql file — autocomplete, CodeLens, and the Parents/Children/Tests panel activate automatically

Column autocomplete: what it needs

Column suggestions come from two independent paths, which explains why they sometimes appear and sometimes don't:

You type	Where the columns come from	Requires
`my_cte.`	The CTE's own `SELECT` list, parsed from the open file	Nothing — works offline, on an unbuilt model
`m.` where `m` aliases a model/source	`catalog.json`	`dbt docs generate`, and the model must have been built

Two things trip people up:

catalog.json is only written by dbt docs generate. Neither dbt compile, nor dbt run, nor dbt build produces or refreshes it. A model can be perfectly compiled and still have no column suggestions. Use the Generate Docs button, then re-run it whenever columns change.
The alias is mandatory. from {{ ref('orders') }} o gives you o.; from {{ ref('orders') }} with no alias gives you nothing to type before the dot.

Also note that the alias must sit right after a single-argument ref()/source() call — ref('package', 'model'), ref('model', version=2), and calls split across lines aren't detected yet.

If nothing is suggested, dbt Forge stays silent rather than guessing. Check those conditions in order.

Architecture

Layer	Stack
Extension Host	TypeScript + VS Code Extension API
Lineage Webview	React + React Flow + dagre (auto-layout), bundled locally — no CDN
Data Source	Reads `manifest.json` / `catalog.json` / `target/compiled/*.sql` directly, with a file watcher to stay in sync. `profiles.yml` is read (never written) to list the environments you can switch between
dbt Execution	Runs the `dbt` executable from your configured venv (`Scripts/`/`bin/`) in the integrated terminal — except data preview, which spawns `dbt show` directly so it can read the rows back

Commands

Command	Description
`dbtForge.generateDocs`	`dbt docs generate` — writes `catalog.json`, which column autocomplete reads
`dbtForge.refreshIndex`	Re-read `manifest.json` / `catalog.json` from disk (does not run dbt)
`dbtForge.compileFile`	`dbt compile --select path:<file>` for the open file — works even if it isn't in the manifest yet
`dbtForge.parseProject`	`dbt parse` — regenerates manifest.json without compiling SQL or hitting the warehouse
`dbtForge.compileProject`	`dbt compile` for the whole project
`dbtForge.buildModel`	`dbt build --select model` for the open model, without upstream or downstream
`dbtForge.buildUpstream`	`dbt build --select +model` for the open model
`dbtForge.buildDownstream`	`dbt build --select model+` for the open model
`dbtForge.testModel`	`dbt test --select model` for the open model
`dbtForge.buildProject`	`dbt build` for the whole project
`dbtForge.buildFolder`	`dbt build --select path:<folder>` for all models in a right-clicked folder
`dbtForge.buildFolderUpstream`	`dbt build --select +path:<folder>` — folder's models + upstream parents
`dbtForge.buildFolderDownstream`	`dbt build --select path:<folder>+` — folder's models + downstream children
`dbtForge.buildTag`	`dbt build --select tag:<tag>` — every resource carrying the tag
`dbtForge.buildTagUpstream`	`dbt build --select +tag:<tag>` — the tag's resources + upstream parents
`dbtForge.buildTagDownstream`	`dbt build --select tag:<tag>+` — the tag's resources + downstream children
`dbtForge.testTag`	`dbt test --select tag:<tag>`
`dbtForge.refreshTags`	Re-read the tag list from the loaded manifest
`dbtForge.previewCompiledSql`	Open the compiled SQL for the open model, read-only
`dbtForge.previewData`	`dbt show` for the open model — rows land in the Data Preview panel (`Ctrl+Enter` / `Cmd+Enter`)
`dbtForge.previewCte`	`dbt show` for one CTE of the open model — invoked from the CodeLens on the CTE itself
`dbtForge.rerunPreview`	Re-run the last data preview
`dbtForge.showLineage`	Open the interactive lineage graph for the open model, seed or snapshot
`dbtForge.selectProfile`	Switch the profile/target dbt Forge runs dbt with (also on the status bar)

Configuration

Setting	Default	Description
`dbtForge.pythonPath`	`""`	Path to the Python executable inside your dbt project's venv. Empty falls back to `dbt` on PATH
`dbtForge.projectDir`	`""`	Path to the dbt project root. Auto-detected (including nested inside a larger workspace) if left empty
`dbtForge.manifestPath`	`target/manifest.json`	Path to manifest.json, relative to the project root
`dbtForge.catalogPath`	`target/catalog.json`	Path to catalog.json, relative to the project root
`dbtForge.compiledDir`	`target/compiled`	Path to the compiled models directory, relative to the project root
`dbtForge.profilesDir`	`""`	Directory holding `profiles.yml`, for the environment picker. Empty looks where dbt does: `DBT_PROFILES_DIR`, the project root, then `~/.dbt`. When set, it is also passed as `--profiles-dir`
`dbtForge.previewRowLimit`	`100`	Rows a data preview asks dbt for (`dbt show --limit`). `-1` fetches every row

Local Data & Privacy

dbt Forge does not collect any data and has no network calls of its own:

Reads manifest.json, catalog.json, and compiled SQL directly from your project's target/ folder
Reads profiles.yml to list the profiles and targets you can switch between. It is only ever read, never modified, and nothing from it — credentials included — leaves your machine or is written to your settings; switching environments only changes the --profile/--target flags on the command line
Your environment choice is stored in VS Code's workspace state, not in a committed .vscode/settings.json
Runs dbt through your own configured Python environment, in your own integrated terminal
Data preview queries your warehouse — it runs dbt show through your own venv and your own profile, so rows travel between your warehouse and your machine exactly as they would if you ran dbt show yourself. The extension stores no credentials and opens no connection of its own, but a preview is not an offline operation: it costs a query against whichever target you are pointed at
No telemetry, no backend, no external service — everything happens on your machine

Roadmap

✅ Core (v1)

ref()/source() autocomplete, Go to Definition, column autocomplete (aliases + CTEs), Parents/Children/Tests panel, build/test shortcuts, compiled SQL preview, interactive lineage graph.

✅ v0.4

Find All References and Go to Definition for macros, in addition to models/sources.

✅ v0.5

Environment switching: pick a profile/target from the status bar, and every dbt command runs against it.

✅ v0.6

Generate Docs command, so the catalog.json column autocomplete depends on can be produced from the editor.

✅ v0.7

Hover documentation for models/sources/macros, and Problems-panel diagnostics for broken ref()/source() calls.

✅ v0.8

Single-file compile (dbt compile --select path:<file>) and dbt parse so a just-created model gets indexed without a full-project run, an actionable welcome view on the relatives panel, and immediate panel/CodeLens refresh on manifest reload.

✅ v0.9

Tags panel: build or test every resource carrying a tag, straight from the sidebar.

✅ v0.10

Data preview: dbt show for the open model or any of its CTEs, rendered in a Data Preview tab in the bottom panel.

✅ v0.11

ref() resolving to seeds and snapshots (not models only), lineage that opens on a seed, node boxes sized from their own name, and lineage nodes showing their materialization and node_color.

🔲 Next

Configurable lineage depth / filtering for very large projects
Multi-project workspace polish (multiple dbt projects in one workspace)

Non-goals

dbt Forge stays small on purpose. One question decides what goes in:

Does the feature need to know your dbt project?

If it has to read manifest.json, catalog.json or your dependency graph to be useful, it belongs here — nobody else can do it as well. If it works the same on any SQL file, it is somebody else's extension, and pulling it in would only make this one heavier at doing what it is actually for.

So these are deliberately out of scope, not "not yet":

Not in scope	Use instead
Jinja / SQL syntax highlighting	Better Jinja — mature, and it covers `.sql`, `.yml` and `.md`
SQL formatting and linting	sqlfmt, SQLFluff, or your editor's own formatter
A warehouse browser or general SQL client	A warehouse-specific extension. Data preview here goes through `dbt show` and nothing else — dbt Forge opens no connection of its own
dbt Cloud, remote execution, AI assistance	Not planned in any form. Everything runs locally through your own venv, and nothing leaves your machine (see Local Data & Privacy)

A request that falls on the wrong side of that line is not a bad idea — it is usually a good idea for a different extension. Where the underlying need does touch the project (say, resolving a doc() to the block that defines it, rather than colouring the {% docs %} tag), that is the version worth opening an issue for.

Contributing

The project is under active development.

Fork → branch → PR
Open an issue to discuss a feature before coding
Follow the existing naming conventions

License

Built with ♥ by Evolve

dbt Forge