Skip to main content
Glama
bazinga012

MCP Code Executor

by bazinga012
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Local

Related Servers

Alternatives to MCP Code Executor

No user-submitted related servers found.

    Related Servers

    • Anaconda MCP by anaconda

      Anaconda MCPofficial

      anaconda
      A
      license
      Not graded
      quality
      B
      maintenance
      Exposes conda environment management tools to MCP-enabled AI coding assistants, enabling them to create, modify, and delete environments and packages on your machine.
      4
      BSD 3-Clause

    • Python Sandbox MCP Server

      Ajaja
      F
      license
      Not graded
      quality
      C
      maintenance
      Enables LLMs to execute Python code in a restricted sandbox for calculations and data analysis, without giving them a real shell.
      -

    • Python MCP Sandbox

      JohanLi233
      A
      license
      Not graded
      quality
      D
      maintenance
      An interactive Python code execution environment that allows users and LLMs to safely execute Python code and install packages in isolated Docker containers.
      40
      Apache 2.0

    • mcp-run-isolated-python

      Kigstn
      A
      license
      Not graded
      quality
      A
      maintenance
      Enables LLMs to execute Python code securely in a sandboxed environment. Supports configurable restrictions like no network access and returns results including files.
      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

    A3.8/5.0

    Scored across 9 tools

    Disambiguation5/5

    Each tool has a clearly distinct purpose with no ambiguity. For example, initialize_code_file, append_to_code_file, and read_code_file handle different file operations, while execute_code and execute_code_file target different execution methods. The descriptions explicitly differentiate tools like execute_code (for short snippets) versus the file-based workflow.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern using snake_case, such as append_to_code_file, check_installed_packages, and configure_environment. There are no deviations in naming style or convention across the set, making them predictable and readable.

    Tool Count5/5

    With 9 tools, the count is well-scoped for a code execution server. Each tool earns its place by covering distinct aspects like file management, environment configuration, dependency handling, and code execution, without being overly sparse or bloated.

    Completeness5/5

    The tool set provides complete coverage for the code execution domain, including CRUD-like operations for files (initialize, append, read), environment management (configure, get config, install dependencies), and execution (code snippets, files). There are no obvious gaps, and the workflow from file creation to execution is fully supported.

    Maintenance

    ActivityInactive
    ResponsivenessUnresponsive

    Resources