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Alternatives to mesa-clm

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    Related Servers

    • A
      license
      A
      quality
      C
      maintenance
      Enables AI assistants to query, modify, and reason over OWL/TTL/RDF ontology files using natural language, without needing SPARQL or OWL syntax.
      14
      5
      MIT
    • F
      license
      Not graded
      quality
      B
      maintenance
      Enables users to search and retrieve research datasets via natural language queries, with tools for proposing and committing tag changes. Includes robust authorization, idempotent mutations, and an audit trail.
      -
    • A
      license
      Not graded
      quality
      Not graded
      maintenance
      Enables AI assistants to navigate and populate complex ontologies by transforming unstructured data into structured, SHACL-validated knowledge graphs. It features semantic hybrid search and proactive schema guidance to help users build deeply linked, reasoning-ready data.
      -
    • A
      license
      Not graded
      quality
      A
      maintenance
      Enables natural language search and discovery of open-access scientific datasets through the EOSC Data Commons OpenSearch service. Provides tools to search datasets and retrieve file metadata using LLM-assisted queries.
      15
      MIT

    TDQS

    B3.2/5.0

    Scored across 50 tools

    Disambiguation3/5

    Most tools have distinct resource+action targets, but several pairs overlap: ds_list_directory vs ds_list_directory_details, ds_search_files_by_avu vs ds_search_metadata (both AVU search), ds_list_avus vs ds_get_metadata, and ds_add_avu vs ds_add_avus. The detailed descriptions do help an agent choose, and the mesa_* vs ds_* split separates higher-level workflows from raw iRODS ops, but the boundaries are not crisp.

    Naming Consistency4/5

    A consistent verb_noun snake_case pattern (ds_add_avu, ds_delete_file, ds_make_directory, ds_list_rules) holds across the dominant ds_ family, with namespace prefixes (mesa_ols_, mesa_avu_, mesa_datacite_, mesa_policy_) grouping related tools predictably. Minor deviations exist, e.g. singular/plural drift (ds_add_avu vs ds_add_avus, ds_list_avus) and redundant qualifiers (ds_search_files_by_avu vs ds_search_metadata).

    Tool Count2/5

    50 tools is very heavy and near the extreme end of the scale. While the surface genuinely spans multiple subsystems (iRODS CRUD, AVUs, tickets, policies, OLS ontologies, DataCite, DuckLake), the count suggests feature bloat and several entries are documented stubs (ds_get_policy_config, ds_get_rule_definition, ds_list_rules) that dilute the set.

    Completeness4/5

    Coverage is broad and near-complete: file/directory CRUD, AVU CRUD and search, ticket lifecycle, access and inheritance management, ontology lookup/hierarchy, DataCite validation/export, and project enrollment all exist. Gaps are minor (some PCF/rule inspection is a documented stub), and agents have viable workarounds via rules and search tools.

    Maintenance

    ActivityMaintained
    ResponsivenessUnresponsive