What prerequisites are needed to use this server?
You need a dbt Cloud account with Semantic Layer enabled, API access to your dbt Cloud instance, and Node.js v14 or later.
@TommyBez
Basic information
MCP Server for querying DBT Semantic Layer
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"dbt-semantic-layer-mcp-server": {
"command": "npx",
"args": [
"-y",
"@smithery/cli",
"install",
"@TommyBez/dbt-semantic-layer-mcp",
"--client",
"claude"
]
}
}
}Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
Fetch the live tool list by running this server in a temporary sandbox using the button above.
The dbt Semantic Layer MCP Server is a Model Context Protocol server that enables querying the dbt Semantic Layer through AI assistants like Claude Desktop. It acts as a bridge to explore, query, and visualize dbt metrics using natural language, providing a single source of truth for business metrics.
Install via Smithery (recommended) using the command npx -y @smithery/cli install @TommyBez/dbt-semantic-layer-mcp --client claude. You need a dbt Cloud account with Semantic Layer enabled and API access, plus Node.js v14 or later. After configuration, ask natural language questions about metrics from Claude Desktop.
You need a dbt Cloud account with Semantic Layer enabled, API access to your dbt Cloud instance, and Node.js v14 or later.
The recommended installation method is via Smithery using the command `npx -y @smithery/cli install @TommyBez/dbt-semantic-layer-mcp --client claude`.
Verify that your API credentials are correct, ensure your dbt Cloud project has Semantic Layer enabled, and check that your metrics are properly defined in your dbt project.
Yes, the server is described as compatible with Claude Desktop and other compatible AI assistants.
You can ask about available metrics, query specific metrics with filters and groupings (e.g., time periods, product categories), and analyze trends like week-over-week growth.

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