"Information about dbt (Data Build Tool or other meanings)" matching MCP servers:

A MCP (Model Context Protocol) server for interacting with dbt.

Enables AI agents to index and search across SQLite databases and CSV files to discover table schemas and column metadata. It provides a unified MCP API for data source management and structural exploration through natural language.

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

MCP server that provides OpenRouter model pricing data, enabling price lookups, trending/cheapest lists, and model searches without an API key.

Enables AI assistants to audit dbt project health, profile warehouse data, detect schema drift, and safely generate or update dbt documentation and tests through natural language.

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.

Enables an agent to run a build tool and receive clean structured compiler diagnostics with file, line, severity, and message, avoiding noisy log spam.

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

Enables AI agents to search and discover data across SQLite and CSV sources through an MCP interface, with metadata indexing and fuzzy search capabilities.

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.

Enables AI assistants to audit, profile, and govern dbt projects through natural language, including coverage scoring, schema drift detection, test suggestions, and non-destructive YAML documentation updates.

Enables AI assistants to audit dbt project health, profile data, detect schema drift, suggest tests, and auto-generate documentation through natural language. It consolidates coverage analysis, data profiling, and safe YAML updates into a single MCP interface.

Enables AI assistants to audit dbt project coverage and health, profile warehouse data, detect schema drift, suggest tests, and generate or safely update model documentation through natural language.

Enables AI assistants to audit dbt project health, profile warehouse data, detect schema drift, and auto-generate documentation and test suggestions through natural language. It provides tooling for coverage scoring, batched column statistics, and non-destructive schema.yml updates.

Enables AI assistants to audit dbt project health, profile warehouse data, detect schema drift, and auto-generate documentation through natural language. It combines coverage scoring, test suggestions, and non-destructive YAML updates in a single MCP server.

Enables AI coding assistants to assess dbt project health and test/documentation coverage, profile warehouse data, detect schema drift, suggest tests, and safely update schema.yml documentation through natural language.

Enables AI assistants to audit dbt project health and test coverage, profile data-warehouse columns, detect schema drift, and safely generate documentation and test suggestions into schema.yml files. It runs read-only warehouse queries and non-destructive YAML merges, all through natural-language conversation in Claude Desktop, Cursor, or other MCP clients.

It enables AI assistants to audit dbt project health, profile data, detect schema drift, suggest tests, and auto-generate documentation through natural language.

Enables AI assistants to audit dbt project health, profile warehouse data, detect schema drift, suggest tests, and safely generate or update schema.yml documentation through natural language.