Skip to main content
Glama
ledror

ipython2-mcp

by ledror
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

Related Servers

Alternatives to ipython2-mcp

No user-submitted related servers found.

    Related Servers

    • Python REPL MCP Server

      piplin-es
      A
      license
      Not graded
      quality
      D
      maintenance
      Provides a persistent Python REPL session as a tool for executing code, managing files, installing packages, and initializing projects via the MCP protocol.
      1
      MIT

    • ipython-mcp

      husams
      A
      license
      B
      quality
      B
      maintenance
      Provides a persistent, stateful IPython execution environment for MCP clients, allowing agents to run Python code, define functions and classes, and maintain state across calls. It includes tools for execution, inspection, dynamic tool registration, and robust timeout/recovery handling.
      11
      MIT

    • Sandbox Agent

      eduresser
      A
      license
      A
      quality
      C
      maintenance
      Enables code execution in isolated Docker containers with persistent IPython, Node.js, or R kernels, supporting file import/export and cross-session transfers via MCP tools.
      6
      MIT

    • mcp-async-repl

      jnotsknab
      A
      license
      Not graded
      quality
      D
      maintenance
      Async Python REPL + Shell execution for MCP. Provides persistent state, background jobs, interactive input() bridging, and crash isolation in a single server.
      1
      Apache 2.0

    • Sherlog MCP

      GetSherlog
      A
      license
      Not graded
      quality
      D
      maintenance
      Provides persistent IPython shell sessions per conversation with DataFrame-centric architecture, enabling stateful data analysis, CLI tool execution, and integration of external MCP servers within the same workspace context.
      23
      Apache 2.0
    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

    A4.3/5.0

    Scored across 6 tools

    Disambiguation5/5

    Each tool maps to a distinct lifecycle action: dependency install, session start, stop, status, code execution, and tab-completion. There is no overlap or ambiguity between tool purposes.

    Naming Consistency5/5

    All tools share the ipython_ prefix and use clear snake_case verb-based suffixes: install_deps, start, stop, status, run, complete. The naming pattern is fully consistent and predictable.

    Tool Count5/5

    Six tools is well-scoped for a session-management server. Every tool covers a necessary part of the workflow without redundancy or bloat.

    Completeness5/5

    The toolset covers the full lifecycle: dependency setup, session creation, inspection, execution, completion, and cleanup. Restarting a session is possible by combining stop and start, so there are no obvious dead ends.

    Maintenance

    ActivitySlowing
    ResponsivenessNo issues

    Resources