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URL: https://glama.ai/mcp/servers/integrations/dbt

⇱ dbt | Glama

  • Why this server?

    Integrates with dbt pipelines to run data quality checks as part of transformation workflows.

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    Agentic data quality MCP server — runs structured validation rules against warehouses (DuckDB, BigQuery, Athena, Databricks, Postgres), diagnoses failures with LLM root cause analysis, and proposes SQL remediations. Full audit trail of every AI decision.
    Last updated
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    Apache 2.0

  • Why this server?

    Provides tools to interact with dbt, including executing dbt CLI commands (build, compile, run, test), accessing Semantic Layer for metric querying, and using Discovery API to explore models and their relationships in a dbt project.

  • Why this server?

    Provides tools for interacting with a dbt project, enabling AI agents to list models, tests, sources, exposures, macros, runs, check freshness, coverage, and explore the DAG using the project's manifest, run results, and catalog.

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    A read-only MCP server that exposes dbt project artifacts and data quality result tables (BigQuery/Postgres) to LLM clients, enabling deep introspection, run-history analysis, source freshness, test coverage, and lineage walks.
    Last updated
    27
    70
    MIT

  • Why this server?

    Supports dbt tasks in job creation and execution.

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    Exposes Databricks REST APIs as MCP tools for managing and querying a Databricks workspace, including clusters, jobs, SQL, Unity Catalog, and more.
    Last updated
    100
    MIT

  • Why this server?

    Enables interaction with DBT (Data Build Tool) projects, allowing querying of project metadata, inspection of models, sources, and tests, viewing compiled SQL, running DBT commands, and accessing DBT documentation and lineage.

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    Enables AI assistants to interact with DBT (Data Build Tool) projects, allowing them to query project metadata, inspect models and sources, view compiled SQL, and run DBT commands.
    Last updated
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    MIT

  • Why this server?

    Allows AI agents to execute dbt CLI commands and interact with dbt projects. Supports operations like run, test, compile, list resources, debug, install dependencies, and load seed data.

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    A Model Context Protocol (MCP) server that wraps the dbt CLI tool, enabling AI coding agents to interact with dbt projects through standardized MCP tools. Developed by Mammoth Growth.
    Last updated
    9
    18
    MIT

  • Why this server?

    Works with dbt to automatically profile and monitor data models after runs.

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    Zero-config data quality monitoring as MCP tools. Profiles a warehouse (Postgres, BigQuery, Snowflake, MySQL, DuckDB), detects anomalies, and gates CI — read-only with the connection resolved server-side, never via the model.
    Last updated
    6
    6
    MIT

  • Why this server?

    Integrates with dbt projects to auto-detect schema definitions and semantic layers for curated querying.

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    SchemaBrain is an MCP server that sits between AI agents (Claude, Cursor, Windsurf) and your SQL database as a read-only trust + intelligence layer. The agent never writes SQL — 12 tools compile it from definitions you control, PII and secret categories are refused before the query runs, and every call lands in a tamper-evident (SHA-256-chained) audit log. Postgres today.
    Last updated
    12
    8
    Apache 2.0

  • Why this server?

    Parses dbt manifests and projects as semantic sources via the ingest_source tool, enabling AI agents to work with dbt models, schemas, and business definitions for generating safe SQL queries.

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    Give AI agents structured database intelligence. Deterministic SQL, NULL trap detection, EXPLAIN pre-flight. MIT licensed.
    Last updated
    1
    MIT