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Alternatives to cellpy-mcp

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    Related Servers

    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables LLM clients to run Python code in a persistent, user-selected interpreter via MCP, with tools for data loading, summaries, regressions, diagnostics, and plotting, while keeping sessions alive between calls and isolating crashes.
      12 PyPI
      MIT
    • F
      license
      Not graded
      quality
      C
      maintenance
      Enables LLM clients to load, clean, visualize, and analyze tabular datasets, and to generate multi-format analytic reports through natural language instructions.
      -
    • A
      license
      Not graded
      quality
      D
      maintenance
      Enables data analysis and visualization operations such as loading CSV/Excel/JSON files, computing summary statistics, generating charts, and exploring datasets via SSE/HTTP.
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables AI agents to drive a live Blender session over stdio, inspecting the scene graph, searching and calling operators, reading and writing RNA properties, rendering viewable images, and checkpointing or restoring the file across a multi-turn conversation. It also exposes gallery and scene-reset helpers so the agent can check its own work and start over cleanly.
      17
      GPL 3.0

    TDQS

    A3.9/5.0

    Scored across 12 tools

    Disambiguation5/5

    Each tool targets a distinct resource or action: listing loaders, cells, and templates; loading; collecting; previewing; exporting; rendering; and API lookup. The list_* and describe_* tools are differentiated by their object type, and the collect/preview/export trio is clearly separated by what it returns or writes.

    Naming Consistency4/5

    Most tools follow a clear verb_noun snake_case pattern (list_cells, load_cell, export_collection, search_api). Minor deviations like 'collect', 'render', and 'new_project' are still readable and predictable, so consistency is high but not perfect.

    Tool Count5/5

    Twelve tools is well-scoped for a domain-specific analysis server. Each tool covers a meaningful part of the cellpy workflow without redundancy or bloat.

    Completeness5/5

    The set covers the full workflow: inspecting environment support, loading cells, building collections, previewing and exporting data, rendering figures, discovering API calls, and creating batch projects. The self-documentation tools fill gaps that would otherwise require external knowledge of cellpy.

    Maintenance

    ActivityMaintained
    ResponsivenessLimited data