Skip to main content
Glama
0x0L

ipykernel-mcp

by 0x0L

Related Servers

Alternatives to ipykernel-mcp

No user-submitted related servers found.

    Related Servers

    • A
      license
      Not graded
      quality
      D
      maintenance
      An MCP server that connects to existing IPython kernels, allowing Claude to execute code in a shared persistent environment with your IDE.
      2
      MIT
    • A
      license
      Not graded
      quality
      D
      maintenance
      An MCP server that gives any MCP-compatible LLM client full control over a live JupyterLab instance.
      MIT
    • F
      license
      A
      quality
      Not graded
      maintenance
      A Model Context Protocol server that allows LLMs to interact with Python environments, enabling code execution, file operations, package management, and development workflows.
      9
      -
    • F
      license
      B
      quality
      F
      maintenance
      An MCP server that manages Python virtual environments using uv, allowing LLMs to reliably resolve dependencies and update virtual environments.
      6
      7
      -
    • A
      license
      B
      quality
      D
      maintenance
      An MCP server that connects directly to a Jupyter kernel via ZMQ, enabling AI assistants to read, create, edit, execute, and manage Jupyter Notebooks as MCP tools.
      9
      MIT

    TDQS

    A4.2/5.0

    Scored across 8 tools

    Disambiguation5/5

    Each tool targets a distinct lifecycle action on the kernel: discover, start, status, restart, interrupt, stop, execute, and get_output. There is no ambiguity between kernel_start/kernel_restart (start launches a new kernel, restart replaces the process while preserving connection), and kernel_execute/kernel_get_output are clearly separated (execute starts, get_output retrieves pending work).

    Naming Consistency5/5

    All tools follow a consistent kernel_verb pattern: kernel_discover, kernel_start, kernel_status, kernel_restart, kernel_interrupt, kernel_stop, kernel_execute, kernel_get_output. The naming convention is uniform and predictable across the entire set.

    Tool Count5/5

    Eight tools is a well-scoped set for a kernel-management MCP server. Each tool covers a distinct and necessary operation for the full kernel lifecycle without redundancy or bloat; the count feels appropriate for the domain.

    Completeness5/5

    The tool surface covers the full kernel lifecycle: discovery, start, status, restart, interrupt, stop, execute, and async output retrieval. The only potential gap is code completion/inspection, but for a kernel-execution server the lifecycle coverage is complete with no dead ends.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues