dbt Semantic Layer MCP Server
@MCP-Mirror
关于 dbt Semantic Layer MCP Server
Mirror of
基本信息
配置
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"TommyBez_dbt-semantic-layer-mcp-server": {
"command": "npx",
"args": [
"-y",
"@smithery/cli",
"install",
"@TommyBez/dbt-semantic-layer-mcp",
"--client",
"claude"
]
}
}
}工具
未检测到工具
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
概览
What is dbt Semantic Layer MCP Server?
An MCP (Model Context Protocol) server that bridges AI assistants like Claude Desktop with the dbt Semantic Layer. It allows users to query business metrics defined in dbt using natural language, enabling metric discovery, data analysis, and result visualization.
How to use dbt Semantic Layer MCP Server?
Install via Smithery (npx -y @smithery/cli install @TommyBez/dbt-semantic-layer-mcp --client claude), then configure it with your dbt Cloud API credentials. Once set up, ask natural language questions about metrics directly from Claude Desktop.
Key features of dbt Semantic Layer MCP Server
- Browse and search available metrics in your dbt Semantic Layer
- Generate and execute semantic queries through natural language
- Filter, group, and order metrics for deeper insights
- Display query results in an easy-to-understand format
Use cases of dbt Semantic Layer MCP Server
- Ask "What metrics are available in my dbt Semantic Layer?" to discover defined metrics
- Query specific metrics like "Show me monthly revenue for the last quarter grouped by product category"
- Analyze trends with questions such as "What's the week-over-week growth in user signups?"
FAQ from dbt Semantic Layer MCP Server
What do I need to use this server?
A dbt Cloud account with the Semantic Layer enabled, API access to your dbt Cloud instance, and Node.js v14 or later.
How do I install the server?
The recommended method is via Smithery: npx -y @smithery/cli install @TommyBez/dbt-semantic-layer-mcp --client claude.
What can I do if queries fail?
Verify your API credentials are correct, ensure your dbt Cloud project has the Semantic Layer enabled, and check that your metrics are properly defined in your dbt project.
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