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dbt MCP — manifest/run_results/sources/catalog parsing + DQ result tables (BigQuery/Postgres)
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dbt MCP — manifest/run_results/sources/catalog parsing + DQ result tables (BigQuery/Postgres)
Security Report
10.0
Low Risk10.0Low RiskValid MCP server (3 strong, 3 medium validity signals). No known CVEs in dependencies. Package registry verified. Imported from the Official MCP Registry.
9 files analyzed · 1 issue found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
Permissions Required
This plugin requests these system permissions. Most are normal for its category.
What You'll Need
Set these up before or after installing:
Path to dbt project root (where dbt_project.yml lives).
Environment variable: DBT_PROJECT_DIR
dbt target dir for manifest.json/run_results.json (default: $DBT_PROJECT_DIR/target).
Environment variable: DBT_TARGET_DIR
Optional dir for archived run_results.json history (glob-scanned).
Environment variable: DBT_RUN_HISTORY_DIR
DQ result table backend: 'bigquery' (default) or 'postgres'.
Environment variable: DQ_BACKEND
Fully qualified DQ checks table, e.g. 'project.data_ops.quality_checks'.
Environment variable: DQ_RESULTS_TABLE
Fully qualified DQ score-daily table, e.g. 'project.data_ops.quality_score_daily'.
Environment variable: DQ_SCORE_TABLE
Service account key path for BigQuery (ADC fallback supported).
Environment variable: GOOGLE_APPLICATION_CREDENTIALS
Explicit BigQuery project ID for DQ queries.
Environment variable: BQ_PROJECT_ID
Postgres connection string when DQ_BACKEND=postgres.Required
Environment variable: PG_CONNECTION_STRING
Reserved for future write tools. Default read-only.
Environment variable: DBT_ALLOW_WRITE
Comma-separated category allowlist (dbt,quality,meta).
Environment variable: DBT_TOOLS
Comma-separated category disablelist.
Environment variable: DBT_DISABLE
How to Install
Add this to your MCP configuration file:
{
"mcpServers": {
"io-github-us-all-dbt": {
"env": {
"DBT_TOOLS": "your-dbt-tools-here",
"DQ_BACKEND": "your-dq-backend-here",
"DBT_DISABLE": "your-dbt-disable-here",
"BQ_PROJECT_ID": "your-bq-project-id-here",
"DBT_TARGET_DIR": "your-dbt-target-dir-here",
"DQ_SCORE_TABLE": "your-dq-score-table-here",
"DBT_ALLOW_WRITE": "your-dbt-allow-write-here",
"DBT_PROJECT_DIR": "your-dbt-project-dir-here",
"DQ_RESULTS_TABLE": "your-dq-results-table-here",
"DBT_RUN_HISTORY_DIR": "your-dbt-run-history-dir-here",
"PG_CONNECTION_STRING": "your-pg-connection-string-here",
"GOOGLE_APPLICATION_CREDENTIALS": "your-google-application-credentials-here"
},
"args": [
"-y",
"@us-all/dbt-mcp"
],
"command": "npx"
}
}
}Documentation
View on GitHubFrom the project's GitHub README.
@us-all/dbt-mcp
dbt MCP server —
manifest.json,run_results.json,sources.json,catalog.json, plus DQ result tables (BigQuery / Postgres) behind one stdio MCP. Built on@us-all/mcp-toolkit.
A read-only window into your dbt project for LLM clients. No dbt run triggering — just deep introspection, run-history analysis, source freshness, per-column test coverage, lineage walks, and (if you have a custom DQ result table) historical check trends and Tier SLA status.
For DAG triggering / run history / log tails, install the companion @us-all/airflow-mcp alongside.
- 22 tools across 3 categories (
dbt,quality,meta) - 4 MCP Prompts for triage workflows
- 4 aggregation tools that replace 3-5 round-trips of "list / get / list"
- Read-only by default
- Hybrid backend: BigQuery (default) or Postgres for DQ result tables — both peer-imported lazily
Install
# 1. add the MCP server
pnpm add -D @us-all/dbt-mcp
# 2. add the DQ backend you actually use (only if you query custom DQ tables):
pnpm add -D @google-cloud/bigquery # OR
pnpm add -D pg
Run
DBT_PROJECT_DIR=/path/to/dbt-project \
DQ_RESULTS_TABLE=my-project.data_ops.quality_checks \
npx @us-all/dbt-mcp
The server speaks MCP stdio; wire it into Claude Desktop / Cursor / any MCP client. Set MCP_TRANSPORT=http to opt in to Streamable HTTP transport (Bearer auth, /health endpoint).
Categories
| Category | Tools | Purpose |
|---|---|---|
dbt | 15 + 2 aggregations | Parse manifest.json / run_results.json / sources.json / catalog.json |
quality | 5 + 2 aggregations | Query quality_checks and quality_score_daily (BQ or PG) |
meta | 1 (always on) | search-tools for natural-language tool discovery |
Toggle with DBT_TOOLS=dbt (allowlist) or DBT_DISABLE=quality (denylist).
Tools at a glance
dbt (15 + 2)
dbt-list-models, dbt-get-model, dbt-list-tests, dbt-get-test, dbt-list-sources, dbt-get-source, dbt-list-exposures, dbt-list-macros, dbt-get-macro, dbt-list-runs, dbt-get-run-results, dbt-failed-tests, dbt-slow-models, dbt-coverage, dbt-graph, freshness-status, incident-context
quality (5 + 2)
dq-list-checks, dq-get-check-history, dq-failed-checks-by-dataset, dq-score-trend, dq-tier-status, failed-tests-summary, dq-score-snapshot
Prompts
| Prompt | Use when |
|---|---|
investigate-failed-tests | "What's broken in the last 24h?" |
freshness-degradation-triage | "Are any sources stale?" (Tier 1 focus optional) |
dq-trend-report | "Give me a stakeholder-friendly DQ trend report" |
incident-triage | "Triage <model | source>" — bundles all signals |
Environment variables
| Env | Required | Notes |
|---|---|---|
DBT_PROJECT_DIR | yes | dbt project root (where dbt_project.yml lives) |
DBT_TARGET_DIR | no | Defaults to $DBT_PROJECT_DIR/target |
DBT_RUN_HISTORY_DIR | no | Optional dir for archived run_results.json history |
DQ_BACKEND | no | bigquery (default) or postgres |
DQ_RESULTS_TABLE | no | FQN of the checks table (without it, quality category errors at call time) |
DQ_SCORE_TABLE | no | FQN of the score-daily table |
GOOGLE_APPLICATION_CREDENTIALS | no | For BigQuery backend (ADC fallback supported) |
BQ_PROJECT_ID | no | Explicit BQ project (otherwise inferred from ADC) |
PG_CONNECTION_STRING | no | When DQ_BACKEND=postgres (secret) |
DBT_ALLOW_WRITE | no | Reserved for future write tools (none in v0.1) |
DBT_TOOLS / DBT_DISABLE | no | Category toggles |
DQ result-table assumed schema (v0.1)
The quality category assumes columns check_name, check_type, dataset, table_name, status, severity, failure_count, run_at, message on DQ_RESULTS_TABLE, and score_date, scope, tier, completeness_pct, freshness_pct, validity_pct, anomaly_free_pct, overall_score on DQ_SCORE_TABLE. v0.2 will add a configurable column-mapping layer.
Tested-against schemas
- dbt manifest schema v11 / v12 / v13 (others usually parse but a
caveatsline will flag them)
Companion server
For Airflow DAG operations (list, runs, task instances, log tail, trigger, clear), install @us-all/airflow-mcp alongside this server.
Build
pnpm install
pnpm run build # tsc → dist/
pnpm test # vitest
pnpm run smoke # spawns dist/index.js, calls initialize + tools/list (set env first)
License
MIT — see LICENSE.
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