"dbt" matching MCP servers:

AI-driven MCP server that audits, profiles, detects schema drift, and auto-generates documentation for dbt projects, enabling natural language interaction with your dbt project's health.

Enables AI agents to inspect, query, test, and safely fix dbt projects and BigQuery warehouses under policy-enforced controls, with read-only direct queries and dbt-only allowlisted writes.

An MCP server that exposes a dbt project's run state as tools, enabling AI assistants to answer questions like 'is the warehouse healthy?' or 'what broke and why?' via plain English, using read-only access to dbt artifacts and warehouse data.

Enables agents to inspect dbt model semantics, retrieve contracts and lineage, and verify that edits do not change what models mean.

Enables AI clients to automatically investigate dbt test failures, trace root cause through BigQuery lineage, and generate plain-English incident reports.

Enables interaction with dbt projects via the Model Context Protocol for data analysis and insights.

Audits dbt Core projects for migration blockers and generates actionable guidance for migrating to dbt Cloud, including auto-fixing deprecated syntax.

A minimal, extensible MCP server to run dbt models via CLI, HTTP API, or AI interfaces like Claude, with Slack notifications for task completions.

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.

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.

Enables AI agents to query live schema, lineage, and query-context across data warehouses, dbt projects, orchestration systems, and BI tools via MCP tools.

Enables language models to run data-quality checks and profiling on local files, using dbt-style assertions like not_null, unique, relationships, and accepted_values.

Enables Claude to interact with a local DuckDB lakehouse by inspecting Gold table schemas, running read-only SQL queries, and checking dbt pipeline health.

Enables data teams to define and validate metrics through conversation, inspect trust scores and lineage, and export definitions to Looker, Tableau, and dbt.

An MCP server that gives AI agents access to configured databases (PostgreSQL, MySQL, Redshift, SQL Server) with SSH/AWS SSM tunnels, pluggable secret providers, and strict per-instance isolation.

Enables AI agents to safely interact with a SQLite shop database through schema discovery, read-only SQL queries, and pre-built analytics reports like top customers, top products, and revenue summaries.

Enables read-only interaction with an online store's SQLite database over MCP stdio, including table listing, schema inspection, safe read-only SQL execution, and sales analytics. It rejects mutating SQL operations to keep data intact.

Provides direct SQL access to a locally hosted Reactome database, enabling schema discovery, guarded read-only queries, and ergonomic helpers over the full relational schema.

Enables AI to execute SQL queries (SELECT, DML, DDL) on MySQL/MariaDB databases with strong security: connection credentials never exposed to AI, write queries require user approval, read-only connections enforced, and query results limited to 50 rows.

Enables AI agents to read-only query an online store's SQLite database, listing tables, inspecting schemas, and running SELECT queries over customers, products, orders, and order items.