Skip to main content
Glama
Try3D

JupyterMCP

by Try3D
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

Related Servers

Alternatives to JupyterMCP

No user-submitted related servers found.

    Related Servers

    • notebook-agent-mcp

      KJH-Sun
      F
      license
      Not graded
      quality
      D
      maintenance
      Enables AI agents to execute Jupyter notebook cells with persistent kernel state, output persistence, and structured JSON control surface.
      2
      -

    • Jupyter MCP Server

      block
      A
      license
      A
      quality
      D
      maintenance
      Enables AI agents to interact with Jupyter notebooks via MCP tools for querying, modifying, executing, and setting up notebooks, with state preservation and real-time collaboration.
      4
      46
      Apache 2.0

    • easy-jupyter-editor-mcp

      cshara1
      F
      license
      Not graded
      quality
      D
      maintenance
      Enables AI agents to safely and structurally edit Jupyter Notebook (.ipynb) files by providing tools to read, edit, add, and delete cells without corrupting the JSON structure.
      1
      -

    • universal-notebook-mcp

      am-3
      A
      license
      A
      quality
      D
      maintenance
      Enables AI assistants to read, edit, and execute Jupyter notebook files (.ipynb) with live kernel output, without requiring JupyterLab.
      17
      MIT
    Deploy Server
    One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

    TDQS

    A4/5.0

    Scored across 21 tools

    Disambiguation5/5

    Each tool targets a distinct action or resource: cell, kernel, notebook, remote, or directory. The kernel-related tools are clearly differentiated (interrupt vs restart vs start), and similarly for cells and notebooks. There is no functional overlap that could confuse an agent.

    Naming Consistency5/5

    All tool names follow a consistent 'resource_verb' pattern: e.g., cell_add, kernel_restart, notebook_get, remote_connect, set_notebook_directory. The naming is uniform and predictable, making it easy for an agent to infer tool purposes.

    Tool Count4/5

    With 21 tools, the set is comprehensive but not excessive. The number is appropriate given the need to cover notebook CRUD, cell manipulation, kernel management, remote connectivity, and directory handling. It is slightly on the high side but remains well-scoped.

    Completeness5/5

    The tool surface covers all essential notebook operations: create/read/update/delete for notebooks and cells, execution (single cell and whole notebook), kernel lifecycle (start, restart, interrupt, status, list), remote server connection for execution, and workspace directory management. There are no obvious gaps.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

    Resources