semantic-mcp
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- AlicenseNot gradedqualityCmaintenanceEnables agents to answer analytics questions with provable correctness by resolving metrics through the semantic layer, tracing lineage, traversing knowledge graphs, checking freshness, and searching glossary definitions, while enforcing access controls and logging every call.MIT
- AlicenseNot gradedqualityAmaintenanceEnables AI agents to query DuckDB, Postgres, and BigQuery through a governed, read-only layer with a semantic model, SQL guard, role-based row policies, PII pseudonymization, audit logging, and cost caps.MIT
- AlicenseAqualityCmaintenanceEnables AI agents and their users to ask business questions in plain language and receive governed metric values, breakdowns, share-of-total figures, and the exact parameterized SQL behind them, drawn from a single semantic model rather than ad-hoc SQL. It also lets clients inspect available metrics and their definitions, and preview optimized queries without executing them.4MIT
- AlicenseNot gradedqualityAmaintenanceEnables AI agents to query governed data warehouses through plain language, returning grounded answers with SQL, confidence grades, and signed receipts while enforcing access, testing, and audit controls.252 PyPI17Apache 2.0
- AlicenseNot gradedqualityCmaintenanceEnables AI agents to understand and query your database safely by providing a semantic layer of metadata, with tools to search, explain, validate, and generate safe SQL.2MIT
- AlicenseAqualityFmaintenanceA governed SQL gateway that exposes typed tools to AI agents, compiling safe read-only queries from a semantic layer while blocking PII before execution, supporting SQL Server, Postgres, and SQLite.9MIT
TDQS
Scored across 4 tools
Each tool has a clearly distinct role: list_metrics enumerates the vocabulary, describe_metric gives the full contract for one metric, query_metric executes it, and explain_lineage traces its dbt provenance. The list-vs-describe overlap is mitigated by the descriptions specifying different granularity and by explicit guidance to start with list_metrics.
All four tools follow a uniform verb_noun snake_case pattern (list_metrics, describe_metric, query_metric, explain_lineage). The convention is predictable and readable throughout, with no mixing of styles.
Four tools is well-scoped for a semantic-layer contract server: discovery, definition, execution, and lineage each earn their place. There is no redundant or filler tool.
The surface covers the full read lifecycle of a metric (discover, inspect, query, trace lineage), which is appropriate for a read-only semantic contract. A minor gap is the lack of a way to enumerate valid dimension/filter values (e.g. distinct dimension members) to help build recortes.