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Alternatives to Safe Code Sandbox

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    Related Servers

    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables MCP-capable agents to execute generated Python, Node.js, or shell code inside disposable, network-isolated Docker containers with strict resource, filesystem, privilege, and time limits, returning structured results and errors.
      MIT
    • A
      license
      Not graded
      quality
      D
      maintenance
      Enables LLMs to safely execute code in isolated Docker containers with resource limits and security controls, supporting session management and automatic dependency installation.
      13 PyPI
      MIT
    • F
      license
      Not graded
      quality
      D
      maintenance
      Enables AI agents to safely execute Python, JavaScript, and Bash code in an isolated Docker sandbox with strict security constraints.
      1
      -
    • A
      license
      A
      quality
      B
      maintenance
      Enables AI coding agents to safely run commands, install dependencies, test, and modify code inside disposable, policy-enforced Docker sandboxes isolated from the host, returning results and diffs.
      15
      MIT
    • F
      license
      Not graded
      quality
      D
      maintenance
      Enables safe Python code execution in isolated Docker containers through the AgentRun framework. Provides automatic container lifecycle management and comprehensive error handling for secure and reproducible code execution.
      -

    TDQS

    A4.2/5.0

    Scored across 3 tools

    Disambiguation5/5

    Each tool has a clearly distinct role in the run lifecycle: start_run launches execution, get_result polls or collects output, and stop_run cancels. There is little risk of confusing one for another, even though get_result and stop_run both report status in some cases.

    Naming Consistency5/5

    All three tools follow a consistent verb_noun pattern: start_run, get_result, stop_run. The naming is predictable and readable.

    Tool Count5/5

    Three tools are well-scoped for an asynchronous sandbox execution model: launch, poll, and cancel. Each tool earns its place without unnecessary surface area.

    Completeness4/5

    The core lifecycle is covered: start, poll for results, and cancel. Minor gaps include no list_runs or explicit artifact/output-file retrieval beyond stdout and stderr, but these are workable for the stated purpose.

    Maintenance

    ActivityMaintained
    ResponsivenessNo recent community issues