Skip to main content
Glama

Related Servers

Alternatives to precis-mcp

No user-submitted related servers found.

    Related Servers

    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables language models to run data-quality checks and profiling on local files, using dbt-style assertions like not_null, unique, relationships, and accepted_values.
      MIT
    • A
      license
      Not graded
      quality
      A
      maintenance
      Local-first MCP server for data quality that finds suspicious data, explains findings with evidence, tracks drift, and supports human-approved, reversible repair workflows. Deterministic by default, with AI optional.
      108 PyPI
      2
      Apache 2.0
    • A
      license
      A
      quality
      A
      maintenance
      Zero-config data quality monitoring as MCP tools. Profiles a warehouse (Postgres, BigQuery, Snowflake, MySQL, DuckDB), detects anomalies, and gates CI — read-only with the connection resolved server-side, never via the model.
      6
      52 PyPI
      11
      MIT
    • A
      license
      A
      quality
      C
      maintenance
      Enables a language model to run four deterministic data checks it cannot argue with — column-contract validation with an explicit quarantine list, arithmetic reconciliation of opening/movements/closing, distinct entity counting against row counts, and duplicate detection returned for human review — each answering with structured findings and row/column locators. Failures come back as results with reasons, so the model reports exactly which rows and columns are broken rather than asserting the data is clean.
      4
      MIT

    TDQS

    A4.4/5.0

    Scored across 4 tools

    Disambiguation4/5

    Each tool has a largely distinct purpose: validate_data checks data, check_config inspects a project's config files, describe_constraints serves as generic reference documentation, and infer_schema produces draft schemas. The main overlap is between validate_data and check_config, since both are used for diagnosing failures, but the descriptions explicitly frame check_config as the follow-up to a validate_data failure, which mitigates most confusion.

    Naming Consistency5/5

    All four tools follow a clean verb_noun snake_case convention: validate_data, check_config, describe_constraints, infer_schema. There are no deviations or mixed conventions.

    Tool Count4/5

    Four tools is a good fit for a focused validation/diagnostics server; each tool serves a clear purpose (validate, diagnose config, reference docs, infer schema). It is on the lighter side, so slightly under-scoped but not thin enough to be a problem.

    Completeness4/5

    The read-only validation lifecycle is well covered: validate, diagnose, reference constraint types, and draft schemas. Minor gaps exist, such as no tool to inspect an existing saved schema or enumerate a project's declared constraints, but these are workarounds rather than blockers.

    Maintenance

    ActivityActive
    ResponsivenessNo issues