Semantic Metrics Modeling Assistant

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The Semantic Metrics Modeling Assistant is a powerful Model Context Protocol (MCP) agent designed to tackle common challenges like metric proliferation, trust deficits, and fragmented governance in data teams. It provides a conversational interface for natural metric definition, sophisticated trust indicators with persistent storage, and visual feedback on lineage and dependencies. By automating governance, offering transparency through multi-dimensional trust scores, and integrating seamlessly with popular BI tools such as Looker, Tableau, and dbt, this assistant significantly reduces cognitive load and fosters confidence in critical data assets.

Características Principales

• Conversational Metric Definition for natural language interaction
• Enhanced Trust Scoring with weighted algorithms, time-decay, and trend analysis
• BI Tool Integrations for Looker (LookML), Tableau (TDS), and dbt (YAML)
• Visual Lineage & Dependencies using Mermaid diagrams and ASCII trees
• Enterprise Data Persistence with SQLite, audit trails, and change tracking
• 2 GitHub stars

Casos de Uso

• A data team member defines a new metric, ensuring it's trusted and consistently applied across the organization.
• An analytics engineer compares different revenue metric definitions to resolve reporting discrepancies across dashboards.
• A data leader identifies which high-usage, low-trust metrics require immediate governance improvements and monitoring.