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.
Enables the analysis of DBT manifests with automatic schema version detection and lineage tracking, allowing users to query model dependencies, access compiled code, and get detailed model information.
A production-ready MCP server that provides comprehensive dbt project quality assessment for any GitHub repository, enabling AI agents to analyze dbt models, check metadata coverage, and map data lineage.
Enables MCP clients to securely query databases, list tables, inspect table schemas, and test connections across Oracle, SQL Server, MySQL, PostgreSQL, and SQLite using read-only SQL tools.
An MCP server for Oracle that won't get you fired...
This MCP server does not expose a SQL prompt, and can't tell you how to log into Oracle. Only the selected objects and SQL statements are usable.
Enables LLMs to safely query databases through a secure gateway that masks PII, enforces role-based table access, rate limits requests, and logs all queries, with Prisma support.
A multi-database MCP server that enables LLMs to safely interact with MySQL, PostgreSQL, SQLite, and others through a unified tool interface, with permission modes and schema resources.
A Model Context Protocol (MCP) server that gives AI assistants deep visibility into databases, inspecting schemas, detecting index problems, analyzing table bloat, and explaining query plans across PostgreSQL, MySQL, and SQLite.
Enables AI agents and assistants to work with a Databricks workspace — SQL, clusters and warehouses, notebooks, Jobs, Lakeflow pipelines, Unity Catalog, Volumes, dashboards, Genie, model serving, Vector Search, Lakebase and Apps — under a safety-first model with read/write/destructive/security classification, confirmation steps for dangerous changes, production resource protection, and a fully read-only mode. Every call is checked against the official Databricks SDK, returns typed schemas and redacted secrets, and unsupported features report an explicit error rather than faking results.
A read-only PostgreSQL MCP server for AI coding agents that exposes database schema and sample data as tools, with LLM-powered semantic search enriched by a user-authored semantic layer.
A typed stdio/HTTP MCP server that lets agents drive governed portfolio-company data onboarding: profiling sources, inferring entities and joins, proposing canonical mappings, generating and sandbox-testing dbt artifacts, and publishing only human-certified results. It exposes agent and reviewer-only tools, tenant-scoped run/ontology/evidence resources, and guided prompts, keeping every calculation deterministic and every approval with a human.
Enables AI tools to interact with Oracle databases through query execution, schema browsing, stored procedure calls, and transaction management. Supports multiple database connections with safety features like read-only mode and dangerous query detection.
A small Python MCP server for querying PostgreSQL and MySQL databases with read-only safety, featuring schema inspection, table description, and query execution tools.
Enables connecting to and querying multiple database types (PostgreSQL, MySQL, SQLite) through a unified interface. Supports managing multiple concurrent database connections with connection pooling and SQL query execution through MCP tools.