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Alternatives to semantic-mcp

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    Related Servers

    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables 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
    • A
      license
      Not graded
      quality
      A
      maintenance
      Enables 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.
      15
      Apache 2.0
    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables 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.
      2
      MIT
    • A
      license
      A
      quality
      F
      maintenance
      A 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.
      9
      MIT
    • A
      license
      A
      quality
      B
      maintenance
      Enables agents to query curated metrics through a registry-backed semantic layer, preventing ad-hoc SQL and enforcing consistent definitions. Every numeric claim is verified against the underlying query result before it is allowed to be sent.
      4
      MIT
    • F
      license
      Not graded
      quality
      B
      maintenance
      Exposes a governed semantic layer built on dbt Core and DuckDB, enabling AI agents to query predefined metric definitions for a P&C insurance dataset. Prevents metric hallucination by restricting agents to governed tools and read-only data access.
      -

    TDQS

    A4/5.0

    Scored across 4 tools

    Disambiguation5/5

    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.

    Naming Consistency5/5

    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.

    Tool Count5/5

    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.

    Completeness4/5

    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.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues