Skip to main content
Glama
questdb

mcp-server-questdb

Official

Related Servers

Alternatives to mcp-server-questdb

No user-submitted related servers found.

    Related Servers

    • A
      license
      Not graded
      quality
      D
      maintenance
      An MCP server that enables AI assistants to interact with q/kdb+ databases for development and debugging workflows. It supports executing queries, persistent connection management, and includes a Qython translator for converting Python-like syntax to q.
      7
      MIT
    • A
      license
      Not graded
      quality
      A
      maintenance
      Quarry provides an MCP server for database querying with safety rails, allowing AI agents to execute SQL queries, list connections, and manage schemas through a structured interface.
      779 PyPI
      3
      MIT
    • A
      license
      A
      quality
      B
      maintenance
      An MCP server that gives AI agents direct read-only access to PostgreSQL databases, enabling natural language analytics through tools for schema exploration, querying, trend analysis, and data quality checks.
      11
      5
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      OctoQuery is an MCP server that converts databases into AI-accessible tools by exposing each configured database as a tool that accepts SQL queries and returns JSON results, enabling AI agents to query your data directly.
      3
      MIT

    TDQS

    A3.6/5.0

    Scored across 35 tools

    Disambiguation3/5

    Most tools target a distinct resource and action, but there is real overlap among list_cells, get_notebook_state, and get_workspace_state—all surface cell lists, statuses, and notebook context. The set_cell_view_maximized / set_cell_maximized pair is also easy to confuse despite different behavior. Detailed descriptions help, but misselection is plausible.

    Naming Consistency4/5

    The set generally follows a clean snake_case verb_noun pattern (get_*, set_*, create_*, delete_*, run_*). Minor deviations exist—get_questdb_toc uses an abbreviation while its counterpart is get_questdb_documentation, and list_cells vs get_tables mixes list with get. Overall the pattern is predictable and readable.

    Tool Count2/5

    35 tools is well beyond the well-scoped range and feels fragmented into micro-operations such as move_cell_up/move_cell_down and two separate maximize tools. The broad QuestDB + notebook domain justifies a large surface, but many operations could be consolidated, making the count heavy.

    Completeness5/5

    The tool surface covers the full domain: documentation lookup, pairing, table metadata, SQL validation and execution, and a complete notebook/cell lifecycle including layout, chart configuration, auto-refresh, and bulk state application. Minor gaps like renaming a notebook or reading cell results directly are workable via run_query and do not create dead ends.