dbt-mcp and dbt-core-mcp
These are competitors offering overlapping functionality—both are MCP servers for dbt project interaction—but the official dbt Labs implementation has substantially higher adoption and likely better integration with dbt's ecosystem, making it the preferred choice for most users.
About dbt-mcp
dbt-labs/dbt-mcp
A MCP (Model Context Protocol) server for interacting with dbt.
Exposes dbt project metadata and operations through 40+ tools across Discovery API, Semantic Layer, SQL execution, and dbt CLI capabilities—enabling AI agents to query lineage, model details, metrics, and trigger jobs. Connects to dbt Core, Fusion, and Platform environments, supporting both local manifest inspection and cloud-based operations with optional column-level lineage analysis via the Fusion engine.
About dbt-core-mcp
NiclasOlofsson/dbt-core-mcp
dbt Core MCP Server: Interact with dbt projects via Model Context Protocol
Executes dbt commands (runs, tests, builds) within the user's actual environment without requiring dbt-core or adapters to be installed server-side, automatically detecting and respecting the Python environment (uv, poetry, venv, conda) and dbt version in use. Integrates with Claude and other MCP-compatible AI assistants via VS Code, providing full project awareness including lineage analysis, compiled SQL inspection, and CTE debugging to enable true pair-programming workflows without context switching.
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